Publications

The Sensors Group publishes in a broad range of disciplines, including IEEE J. Solid State Circuits, IEEE Transactions on Electron Devices, IEEE Transactions on Circuits and Systems, Neural Information Processing Systems (NIPS), Intl. Conf. on Learning Research (ICLR), Current Opinion in Biology, IEEE Pattern and Machine Intelligence (PAMI), European Conference on Signal Processing, ESSCIRC, ISSCC, ISCAS, etc. Below is a selection of recent publications.

You can also look at the publications database of the INI.

2023

Q. Chen, Y. Chang, K. Kim, C. Gao, and S-C. Liu, An area-efficient ultra-low-power time-domain feature extractor for edge keyword spotting, 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023.
G. Haessig, D. Joubert, J. Haque, M. B. Milde, T. Delbruck, and V. Gruev. PDAVIS: Bio-inspired polarization event camera, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3962-3971, 2023.
K. Kim and S-C. Liu, A 3.11 μW 40 nV/√Hz Instrumentation amplifier for bio-impedance sensors exploiting positive-feedback-assisted gain boosting, 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023.
H. Mei, Z. Wang, X. Yang, X. Wei, and T. Delbruck, Deep polarization reconstruction with PDAVIS events, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 22149-22158, 2023.
J. Ott and S-C. Liu, Biologically-inspired continual learning of human motion sequences, 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Jun 4-9, 2023.
A. Rios-Navarro, S. Guo, A. Gnaneswaran, K. Vijayakumar, A. Linares-Barranco, T. Aarrestad, R. Kastner, and T. Delbruck, Within-camera multilayer perceptron DVS denoising, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3932-3941. 2023.
M. Rovira, C. Lafaye, S. Wang, C. Fernandez-Sanchez, M. Saubade, S-C. Liu, and C. Jimenez-Jorquera, Analytical assessment of sodium ISFET based sensors for sweat analysis, Sensors and Actuators B: Chemical, 2023, https://doi.org/10.1016/j.snb.2023.134135.
S. Wang, M. Rovira, C. Jiḿenez-Jorquera, and S-C. Liu, End-to-end prediction of sodium concentration from uncalibrated sodium ISFETs, 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023.
S. Wang*, M. Rovira*, S. Demuru*, C. Lafaye*, J. Kim, B. P. Kunnel, C. Besson., C. F.-Sanchez, P. Serra-Graells, J. M. Margarit, J. Aymerich, J. Cuenca, I. Kiselev, V. Gremeaux, M. Saubade, C. Jiḿenez-Jorquera, D. Briand, and S-C. Liu, Multisensing wearables for real-time monitoring of sweat electrolyte biomarkers during exercise and analysis on their correlation with core body temperature, IEEE Transactions on Biomedical Circuits and Systems, 2023, https://doi.org/10.1109/TBCAS.2023.3286528.
S. Zhou, X. Chen, K. Kim, and S-C. Liu, High-accuracy and energy-efficient acoustic inference using hardware-aware training and a 0.34 nW/ch full-wave rectifier, 2023 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2023. Received AICAS Best Poster Award.

2022

T. Delbruck, C-H. Li, R. Graca, and B. McReynolds, Utility and feasibility of a center surround event camera, Special Session on Neuromorphic and perception-based image acquisition and analysis, 29th IEEE International Conference on Image Processing (ICIP), Oct 2022.
C. Gao, T. Delbruck, and S-C. Liu, Spartus: A 9.4 TOp/s FPGA-based LSTM accelerator exploiting spatio-temporal sparsity, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022. https://arxiv.org/abs/2108.02297v1.
S. Guo and T. Delbruck, Low cost and latency event camera background activity denoising, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2022.3152999.
C. Gao, J. H. Lindmar, and S-C. Liu, Intrinsic sparse LSTM using structured targeted dropout for efficient hardware inference, IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2022.
J. Hadorn*, Z. Wang*, B. Rueckauer, X. Chen, P. Roelfsema, and S-C. Liu, Fast temporal decoding from large-scale neural recordings in monkey visual cortex, Accepted to 4th Shared Visual Representations in Human and Machine Intelligence (SVRHM) NeurIPS workshop, Dec 2022.
Y. Hu, T. Delbruck, and S-C. Liu, Kernel modulation: A parameter-efficient method for training convolutional neural networks, 26th International Conference on Pattern Recognition (ICPR), 2022.
I. Kiselev, G. Gao and S-C. Liu, Spiking cochlea with system-level local automatic gain control, IEEE Transactions on Circuits and Systems-I Regular Papers, 2022, https://doi.org/10.1109/TCSI.2022.3150165.
K. Kim*, C. Gao*, I. Kiselev, T. Delbruck and S-C. Liu, A 23μW solar-powered keyword spotting ASIC with ring-oscillator-based time-domain feature extraction, IEEE International Solid-state Circuits Conference, Feb 2022.
K. Kim, C. Gao, I. Kiselev, T. Delbruck and S-C. Liu, A 23 μW keyword spotting IC with ring-oscillator-based time-domain feature extraction, IEEE Journal of Solid-state Circuits, 2022.
C. Lafaye, M. Rovira, S. Demuru, S. Wang, et al Real-time smart multisensing wearable platform for monitoring sweat biomarkers during exercise, Oral presentation at 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2022.
M. Liu and T. Delbruck, EDFLOW: Event driven optical flow camera with keypoint detection and adaptive block matching, IEEE Transactions on Circuits and Systems for Video Technology, 2022
J.M. Margarit-Taulé, M. Martín-Ezquerra, R. Escudé-Pujol, C. Jiménez-Jorquera and S-C. Liu, Cross-compensation of FET sensor drift and matrix effects in the industrial continuous monitoring of ion concentrations, Sensors and Actuators B: Chemical, volume 353, 2022.
B. McReynolds, R. Graca, and T. Delbruck, Experimental methods to predict dynamic vision sensor event camera performance, Opt. Eng. 61(7) 074103, July 2022.
S. Wang, Y. Hu, and S-C. Liu, T-NGA: Temporal network grafting algorithm for learning to process spiking audio sensor events, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022, https://arxiv.org/abs/2202.03204.
S. Wang, C. Lafaye, M. Saubade, C. Besson, V. Gremeaux, and S-C. Liu, Predicting hydration status using machine learning models from physiological and sweat biomarkers during endurance exercise: a single case study, IEEE Journal of Biomedical and Health Informatics (J-BHI), 2022.
Z. Wang, Y. Hu, and S-C. Liu, Exploiting spatial sparsity for event cameras with visual transformers, 29th IEEE International Conference on Image Processing (ICIP), Oct 2022.
Z. Wang, S. Wang, C. Lafaye, M. Saubade, V. Gremeaux, and S-C. Liu, Person identification using deep neural networks on physiological biomarkers during exercise, Oral presentation at 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2022.

2021

X. Chen, C. Gao, T. Delbruck, and S-C. Liu, EILE: Efficient incremental learning on the edge, 2021 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Jun 6 – 8, 2021.
T. Delbruck, R. Graca, and M. Paluch, Feedback control of event cameras, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW); Third International Workshop on Event-Based Vision, 2021.
Y. Hu, S-C. Liu, and T. Delbruck v2e: From video frames to realistic DVS events, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW); Third International Workshop on Event-Based Vision, 2021. (Runner-up for Best Paper Award at the Workshop)
I. Kiselev and S-C. Liu, Spike-based local gain control on a spiking cochlea sensor, IEEE International Symposium on Circuits and Systems (ISCAS), 2021, https://doi.org/10.1109/ISCAS51556.2021.9401742.
N. Lebow, B. Rueckauer, P. Sun, M. Rovira, C. Jimenez-Jorquera, S-C. Liu and J. M. Margarit-Taulé, Real-time edge neuromorphic tasting from chemical microsensor arrays, Frontiers of Neuroscience, 2021, https://doi: 10.3389/fnins.2021.771480.
Q. Liu, B. Rueckauer, L. Li, T. Delbruck and S-C. Liu, Reducing latency in a converted spiking video segmentation network, IEEE International Symposium on Circuits and Systems (ISCAS), 2021, https://doi.org/10.1109/ISCAS51556.2021.9401667.
B. Rueckauer and S-C. Liu, Temporal pattern coding in deep spiking neural networks, IEEE International Joint Conference on Neural Networks (IJCNN), 2021.
B. Rueckauer and S-C. Liu, Contraction of dynamically masked deep neural networks for efficient video processing, IEEE Transactions on Circuits and Systems for Video Technology, 2021, DOI: https://doi.org/10.1109/TCSVT.2021.3066241.
H. Wang, H. Mohammed, Z. Wang, B. Rueckauer, and S-C. Liu, LiteEdge: Lightweight semantic edge detection network, Proc of the IEEE/CVF International Conference on Computer Vision, ICCV Video Scene Parsing in the Wild (VSPW) workshop, pp. 2657-2666, 2021.

2020

T. Delbruck et al, Confession session: Lessons learned the hard way, IEEE International Symposium on Circuits and Systems (ISCAS), 2020.
E. Ceolini, I. Kiselev, and S-C. Liu, Evaluating multi-channel multi-device speech separation algorithms in the wild: a hardware-software solution, IEEE Transactions on Audio, Language and Speech Processing, 2020, DOI: 10.1109/TASLP.2020.2989545.
E. Ceolini, J. Hjortkjær, D. D.E. Wong, J. O’Sullivan, V. S. Raghavan, J. Herrero, A. D. Mehta, S-C. Liu, and N. Mesgarani, Brain-informed speech separation (BISS) for enhancement of target speaker in multitalker speech perception, NeuroImage, 2020, DOI: 10.1016/j.neuroimage.2020.117282.
C. Gao, A. Rios-Navarro, X. Chen, S-C. Liu, and T. Delbruck, EdgeDRNN: Recurrent neural network accelerator for edge inference, 2020 IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2020, https://doi.org/10.1109/JETCAS.2020.3040300.
C. Gao, R. Gehlhar, A. D. Ames, S-C. Liu, and T. Delbruck, Recurrent neural network control of a hybrid dynamic transfemoral prosthesis with EdgeDRNN accelerator, 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020.
C. Gao, A. Rios-Navarro, X. Chen, T. Delbruck, and S-C. Liu, EdgeDRNN: Enabling low-latency recurrent neural network edge inference, 2020 IEEE Artificial Intelligence on Circuits and Systems, 2020 (Received AICAS best paper award).
Y. Hu, J. Binas, D. Neil, S-C. Liu, and T. Delbruck, DDD20 end-to-end event camera driving dataset: Fusing frames and events with deep learning for improved steering prediction, 23rd Intelligent Transportation Systems Conference (IEEE ITSC 2020), 2020.
Y. Hu, T. Delbruck, and S-C. Liu, Learning to exploit multiple vision modalities by using grafted networks, 16th European Conference on Computer Vision, ECCV 2020, 2020.
I. Lungu, A. Aimar, Y. Hu, T. Delbruck, and S-C. Liu, Siamese networks for few-shot learning on edge embedded devices, 2020 IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2020, https://doi.org/10.1109/JETCAS.2020.3033155.
I. Lungu, Y. Hu, and S-C. Liu, Multi-resolution Siamese networks for one-shot learning, 2020 IEEE Artificial Intelligence on Circuits and Systems, 2020.
Z. Yu and T. Delbruck, Self calibration of wide dynamic range bias current generators, 2020 IEEE International Conference on Circuits and Systems (ISCAS), https://doi.org/10.1109/ISCAS45731.2020.9180623.
S. Wang, Y. Hu, and S-C. Liu, Prediction of gas concentration using gated recurrent neural networks, 2020 IEEE Artificial Intelligence on Circuits and Systems (AICAS), 2020.

2019

S. Braun and S-C. Liu, Parameter uncertainty for end-to-end speech recognition, 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019), 2019 (Received IBM best student paper award).
S. Braun, D. Neil, J. Anumula, E. Ceolini and S-C. Liu, Attention-driven multi-sensor selection, International Joint Conference on Neural Networks, IJCNN 2019, 2019.
E. Calabrese, G. Taverni, C.A. Easthope, S. Skriabine, F. Corradi, L. Longinotti, K. Eng, T. Delbruck, DHP19: Dynamic Vision Sensor 3D Human Pose Dataset, Proceedings of the IEEE Computer Vision and Pattern Recognition Workshops, 2019.
E. Ceolini, J. Anumula, S. Braun, and S-C. Liu, Event-driven pipeline for low latency low compute keyword spotting and speaker verification system,2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019.
E. Ceolini, I. Kiselev, and S-C. Liu, Audio classification systems using deep neural networks and an event-driven auditory sensor, IEEE Sensors Conference, 2019 (Invited).
E. Ceolini and S-C. Liu, Combining deep neural networks and beamforming for real-time multi-channel speech enhancement using a wireless acoustic sensor, IEEE International Workshop on Machine Learning for Speech Processing (MLSP 2019), 2019
T. Delbruck and S-C. Liu, Data-driven neuromorphic DRAM-based CNN and RNN accelerators, 53nd Asilomar Conference on Signals, Systems and Computers), Pacific Grove, CA, Nov 3-6, 2019, https://arxiv.org/abs/2003.13006.
C. Gao, S. Braun, I. Kiselev, J. Anumula, T. Delbruck, and S-C. Liu, Real-time speech recognition for IoT purpose using a delta recurrent neural network accelerator, 2019 IEEE International Symposium on Circuits and Systems, Sapporo, Japan, 2019.
C. Gao, S. Braun, I. Kiselev, J. Anumula, T. Delbruck, and S-C. Liu, Live demonstration: Real-time spoken digit recognition using the DeltaRNN accelerator, 2019 IEEE International Symposium on Circuits and Systems, Sapporo, Japan, 2019.
Y. Hu, T. Delbruck, and S-C. Liu, Incremental learning meets reduced precision networks, 2019 IEEE International Symposium on Circuits and Systems, Sapporo, Japan, 2019.
Y. Hu, H. M. Chen, and T. Delbruck, Slasher: Stadium racer for end-to-end event-based camera autonomous driving experiments. in 2019 IEEE Artificial Intelligence Circuits and Systems, Taiwan, 2019.
A. Huber and S-C. Liu, Filtering of nonuniformly sampled bandlimited functions, IEEE Signal Processing Letters, 2019.
A. Huber, J. Anumula, and S-C. Liu, On the learning of parametric families of distributions with a specific analysis of the Ornstein-Uhlenbeck process, Neural Computation, 2019.
X. Li, D. Neil, T. Delbruck, and S-C. Liu, Lip reading deep network exploiting multi-modal spiking visual and auditory sensors, 2019 IEEE International Symposium on Circuits and Systems, Sapporo, Japan, 2019.
C-H. Li, L. Longinotti, F. Corradi, and T. Delbruck, A 132 by 104 10μm-Pixel 250μW 1kefps Dynamic Vision Sensor with Pixel-Parallel Noise and Spatial Redundancy Suppression, 2019 Symposium on VLSI Circuits, Kyoto, Japan, pp. C216-C217, 2019.
A. Linares-Barranco, F. Perez-Peña, D. P. Moeys, F. Gomez-Rodriguez, G. Jimenez-Moreno, S-C. Liu, and T. Delbruck, Low Latency Event-Based Filtering and Feature Extraction for Dynamic Vision Sensors in Real-Time FPGA Applications, IEEE Access, 7, pp. 134926-134942, 2019.
S-C. Liu, B. Rueckauer, E. Ceolini, A. Huber, and T. Delbruck, Event-driven sensing for efficient perception, IEEE Signal Processing Magazine: Special Issue on Learning Algorithms and Signal Processing for Brain-Inspired Computing, 36 (6), pp. 29-37, Nov. 2019, doi: 10.1109/MSP.2019.2928127.
M. Liu, W-T. Kao, T. Delbruck, Live Demonstration: A Real-Time Event-Based Fast Corner Detection Demo Based on FPGA, Proceedings of the IEEE Computer Vision and Pattern Recognition Workshops, 2019.
I. Lungu, S-C. Liu, and T. Delbruck, Fast event-driven incremental learning of hand symbols, 2019 IEEE Artificial Intelligence Circuits and Systems, Taiwan, 2019.
I. Lungu, S-C. Liu, and T. Delbruck, Incremental learning of hand symbols using an event-driven camera, IEEE Journal on Emerging Techonologies, Circuits and Systems (JETCAS), 2019.
J. M. Margarit-Taulé, P. Giménez-Gómez, R. Escudé-Pujol, M. Gutiérrez-Capitán, C. Jiménez and S-C. Liu, Live demonstration: A portable microsensor fusion system with real-time measurement for on-site beverage tasting, 2019 IEEE International Symposium on Circuits and Systems, Sapporo, Japan, 2019 (Received IEEE ISCAS Runner-up Best Demonstration award).
A. Mitrokhin, C. Ye, C. Fermuller, Y. Aloimonos, and T. Delbruck, EV-IMO: Motion segmentation dataset and learning pipeline for event cameras, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), 2019.
N. de Rita, A. Aimar and, T. Delbruck, CNN-based detection on low precision hardware: Racing car case study, 2019 IEEE Intelligent Vehicles Symposium (IV), pp. 647-652, 2019, doi: 10.1109/IVS.2019.8814001.
B. Rueckauer and S-C. Liu, Linear approximation of deep neural networks for efficient inference on video data, European Conference on Signal Processing, EUSIPCO 2019, Spain, 2019.
M. Żołnowski, R. Reszelewski, D. P. Moeys, T. Delbruck, and K. Kamiński Observational evaluation of event cameras performance in optical space surveillance, ESA NEO SST, 2019.

2018

A. Aimar, H. Mostafa, E. Calabrese, A. Rios-Navarro, R. Tapidor-Morales, J. Lungu, M. Milde, F. Corradi, A. Linares-Barranco, S-C. Liu, and T. Delbruck, NullHop: A flexible convolutional neural network accelerator based on sparse representations of feature maps, IEEE Transactions on Neural Networks and Learning Systems, 2018.
J. Anumula, E. Ceolini, Z. He, A. Huber, and S-C. Liu, An event-driven probabilistic model of sound source localization using cochlea spikes, 2018 IEEE International Symposium on Circuits and Systems, Florence, Italy, 2018.
J. Anumula, D. Neil, T. Delbruck, and S-C. Liu, Feature representations for neuromorphic audio spike streams, Frontiers in Neuroscience, https://doi.org/10.3389/fnins.2018.00023, 2018.
S. Braun, D. Neil, J. Anumula, E. Ceolini, and S-C. Liu, Multi-channel attention for end-to-end speech recognition, Interspeech, Sep 2-6, 2018.
E. Ceolini, J. Anumula, A. Huber, I. Kiselev, and S-C. Liu, Speaker activity detection and minimum variance beamforming for source separation, Interspeech, Sep 2-6, 2018.
C. Chien, L. Longinotti, A. Steimer, and S-C. Liu, Hardware implementation of an event-based message passing graphical model network, IEEE Transactions on Circuits and Systems I, 2018.
G. Gallego, J. E. A. Lund, E. Mueggler, H. Rebecq, T. Delbruck, and D. Scaramuzza, Event-based, 6-DOF camera tracking from photometric depth maps, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018.
C. Gao, D. Neil, E. Ceolini, S-C. Liu, and T. Delbruck, DeltaRNN: A power-efficient recurrent neural network accelerator, 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2018.
A. Huber and S-C. Liu, On approximation of bandlimited functions with compressed sensing, IEEE International International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.
E. Kerr, P. Vance, D. Kerr, S. A. Coleman, G. Das, T. M. McGinnity, D. P. Moeys, and T. Delbruck, Biological goal seeking, IEEE Symposium Series on Computational Intelligence (SSCI), 2018.
A. Linares-Barranco, H. Liu, A. Rios-Navarro, F. Gomez-Rodriguez, D. P. Moeys, and T. Delbruck, Approaching retinal ganglion cell modeling and FPGA implementation for robotics. Entropy 20, 475. doi:10.3390/e20060475, 2018.
D. P. Moeys, D. Neil, F. Corradi, E. Kerr, P. Vance, G. Das, S. A. Coleman, T. M. McGinnity, D. Kerr, and T. Delbruck, PRED18: Dataset and further experiments with DAVIS event camera in predator-prey robot chasing, IEEE Fourth International Conference on Event-Based Control, Communication and Signal Processing (EBCCSP), 2018.
B. Rueckauer and S-C. Liu, Conversion of analog to spiking neural networks using sparse temporal coding, 2018 IEEE International Symposium on Circuits and Systems, Florence, Italy, 2018.
D.P. Moeys, F. Corradi, C. Li, S. A. Bamford, L. Longinotti, F. F. Voigt, S. Berry, G. Taverni, F. Helmchen, and T. Delbruck, A sensitive dynamic and active pixel vision sensor for color or neural imaging applications, IEEE Transactions on Biomedical Circuits and Systems, 12 (1), pp. 123-136, 2018.
G. Taverni, D. P. Moeys, C-H. Li, C. Cavaco, V. Mostnyi, D. Bello, and T. Delbruck, Front and back illuminated Dynamic and Active Pixel Vision Sensor comparison, IEEE Transactions on Circuits and Systems II, Express Briefs, 65, 677–681, 2018.
G. Taverni, D. P. Moeys, C-H. Li, C. Cavaco, V. Mostnyi, D. Bello, and T. Delbruck, Front and back illuminated Dynamic and Active Pixel Vision Sensors comparison, Live Demonstration: 2018 IEEE International Symposium on Circuits and Systems, Florence, Italy, 2018.
G. Taverni, D. P. Moeys, F. Voigt, C-H. Li, C. Cavaco, V. Mostnyi, S. Berry, P. Sipilä, D. Bello, F. Helmchen, and T. Delbruck, Live Demonstration: In-vivo imaging of neural activity with Dynamic Vision Sensors, IEEE BioCAS, 2018.
D. Wong, J. Hjortkjær, E. Ceolini, S. V. Nielsen, S. R. Griful, S. Fuglsang, I. Kiselev, M. Chait, T. Lunner, T. Dau, S-C. Liu, and A. de Cheveigné, A closed-loop platform for real-time attention control of simultaneous sound streams, ARO 2018.

2017

J. Anumula, D. Neil, X-Y. Li, T. Delbruck, and S-C. Liu, Live Demonstration: Event-driven real-time spoken digit recognition system, 2017 IEEE International Symposium on Circuits and Systems, May 28–31, Baltimore, USA, 2017.
A. Amir, B. Taba, D. Berg, Ti. Melano, J. McKinstry, C. Di Nolfo, T. Nayak, Alexander Andreopoulos, G. Garreau, M. Mendoza, J. Kusnitz, M. Debole, S. Esser, T. Delbruck, M. Flickner, and D. Modha, A low power, fully event-based gesture recognition system, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), 7243-7252, 2017.
J. Binas, D. Neil, S-C. Liu, and T. Delbruck, DDD17+: End-to-end DAVIS driving dataset, ICML Workshop on Machine Learning for Autonomous Vehicles 2017, PMLR 70:2584-2593, Aug 6-12, Sydney, Australia, 2017.
S. Braun, D. Neil, and S-C. Liu, A curriculum learning method for improved noise robustness in automatic speech recognition, in 25^th European Signal Processing Conference (EUSIPCO), Aug 28 – Sep 2, Kos Island, 2017.
E. Ceolini and S-C. Liu, Impact of low-precision deep regression networks on single-channel source separation, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Mar 5-9, New Orleans, USA, 2017.
A. Huber and S-C. Liu, On send-on-delta sampling of bandlimited functions, 12^th International Conference on Sampling Theory and Applications (SAMPTA), July 3–7, Tallinn, Estonia, 2017.
I. Kiselev, E. Ceolini, D. Wong, A. de Cheveigne, and S-C. Liu, WHISPER: Wireless synchronized distributed audio sensor platform, 2017 IEEE 42nd Conf on Local Computer Networks (LCN) Workshops, doi: 10.1109/LCN.Workshops.2017.62, 2017.
I.-A. Lungu, F. Corradi, and T. Delbruck, Live demonstration: Convolutional Neural Network driven by Dynamic Vision Sensor playing RoShamBo, in 2017 IEEE Symposium on Circuits and Systems (ISCAS 2017), Baltimore, MD, USA, 2017 [Online]. Available: https://drive.google.com/file/d/0BzvXOhBHjRheYjNWZGYtNFpVRkU/view?usp=sharing.
D. Moeys, C. Li, J. Martel, S. Bamford, L. Longinotti, V. Motsnyi, D. S. S. Bello and T. Delbruck, Color temporal contrast sensitivity in Dynamic Vision Sensors, in 2017 IEEE Symposium on Circuits and Systems (ISCAS 2017), Baltimore, MD, USA, 2017.
D. Neil, J-H. Lee, T. Delbruck, and S-C. Liu, Delta networks for optimized recurrent network computation, International Conference on Machine Learning (ICML), Aug 6-12, Sydney, Australia, 2017.
Y. Nozaki and T. Delbruck, Temperature and parasitic photocurrent effects in Dynamic Vision Sensors, IEEE Transactions on Electron Devices, vol. PP, no. 99, pp. 1–7, 2017.
B. Rueckauer, Y. Hu, I. Lungu, M. Pfeiffer, and S-C. Liu, Conversion of continuous-valued deep networks to efficient event-driven networks for image classification, Frontiers in Neuroscience, doi: https://doi.org/10.3389/fnins.2017.00682, 2017.
G. Taverni, D. Moeys, F. Voigt, C. Li, C. Cavaco, V. Motsnyi, S. Berry, P. Sipilä, D. Bello, F. Helmchen, T. Delbruck, In-vivo Imaging of neural activity with Dynamic Vision Sensors, in 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), Oct 19-22, Turin, 2017.
M. Yang, S-C. Liu, and T. Delbruck, Analysis of encoding degradation in spiking sensors due to spike delay variation, IEEE Transactions on Circuits and Systems I, 61(1), pp. 145-155, 2017.

2016

S. Bhargava, C. Riday, R. Hahnloser, and S-C. Liu, A monaural source separation using a random forest classifier, Interspeech, 2016.
C. Braendli, J. Strubel, S. Keller, D. Scaramuzza, and T. Delbruck, ELiSeD-An event-based line segment detector, IEEE Second International Conference on Event-Based Control, Communication and Signal Processing (EBCCSP), 2016.
S. Braun, D. Neil, and S-C. Liu, A curriculum learning method for improved noise robustness in automatic speech recognition, arXiv preprint, arXiv: 1606.06864, 2016.
E. Ceolini, D. Neil, T. Delbruck, and S-C. Liu, Temporal sequence recognition in a self-organizing recurrent network, IEEE Second International Conference on Event-Based Control, Communication and Signal Processing (EBCCSP), 2016.
T. Delbruck, Neuromorphic vision sensing and processing, 2016 Solid-State Device Research Conference (ESSDERC), 2016.
T Delbruck, Neuromorphic vision sensing and processing, 46th European Solid-State Device Research Conference (ESSDERC), 7-14, 2016.
Y. Hu, H. Liu , M. Pfeiffer, and T. Delbruck, DVS benchmark datasets for object tracking, action recognition and object recognition, Frontiers in Neuromorphic Engineering, 10:(405), 2016.
I. Kiselev, D. Neil and S-C. Liu, Event-driven deep neural network hardware system for sensor fusion, 2016 IEEE International Symposium on Circuits and Systems (ISCAS), 2016.
JH Lee, T. Delbruck, and M. Pfeiffer, Training deep spiking neural networks using backpropagation, Frontiers in Neuromscience, 2016.
H. Liu, D. Moeys, G. Das, D. Neil, S-C. Liu and T. Delbruck, Combined frame- and event-based detection and tracking, 2016 IEEE International Symposium on Circuits and Systems (ISCAS), 2016.
D. Moeys, F. Corradi, E. Kerr, P. Vance, G. Das, D. Neil, D. Kerr, and T. Delbruck, Steering a predator robot using a mixed frame/event-driven convolutional neural network, IEEE Second International Conference on Event-Based Control, Communication and Signal Processing (EBCCSP), 2016.
D. Neil, M. Pfeiffer, and S-C. Liu, Phased LSTM: Accelerating recurrent network training for long or event-based sequences, Advances in Neural Information Processing Systems, Oral Presentation, 2016.
D. Neil, M. Pfeiffer, and S-C. Liu, Learning to be efficient: Algorithms for training low latency, low-compute deep spiking neural networks, ACM Symposium on Applied Computing, 2016.
D. Neil and S-C. Liu, Effective sensor fusion with event-based sensors and deep network architectures, 2016 IEEE International Symposium on Circuits and Systems (ISCAS), 2016.
B. Rueckauer and T. Delbruck, Evaluation of event-based algorithms for optical flow with ground-truth from inertial measurement sensor, Frontiers in Neuroscience, 10:(176) pp. 1-17, 2016.
M. Yang, C-H. Chien, T. Delbruck, and S-C. Liu, A 0.5V 55uW 64X2-channel binaural silicon cochlea for event-driven stereo-audio sensing, 2016 IEEE International Solid-State Circuits (ISSCC), 2016.
M. Yang, C-H. Chien, T. Delbruck, and S-C. Liu, A 0.5V 55uW 64X2-channel binaural silicon cochlea for event-driven stereo-audio sensing, 2016 IEEE Journal of Solid-State Circuits, 51(1), pp. 2554--2569, 2016.

2015

A. Zai, S. Bhargava, N. Mesgarani, and S-C Liu, Reconstruction of audio waveforms from spike trains of artificial cochlea models, Frontiers in Neuromorphic Engineering, 2015
E. Stromatias, D. Neil, M. Pfeiffer, F. Galluppi, S. Furber, and S-C Liu, Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms , Frontiers in Neuromorphic Engineering, 9 (222), 2015.
P. U. Diehl, D. Neil, J. Binas, M. Cook, S-C Liu and M. Pfeiffer, Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing, IEEE International Joint Conference on Neural Networks (IJCNN), 2015.
E. Stromatias, D. Neil, M. Pfeiffer, F. Galluppi, S-C Liu and S. Furber, Scalable energy-efficient, low-latency implementations of spiking Deep Belief Networks on SpiNNaker, IEEE International Joint Conference on Neural Networks (IJCNN), 2015.
M-H. Yang, S-C. Liu, and T. Delbruck, A Dynamic Vision Sensor with 1% temporal contrast sensitivity and in-pixel asynchronous delta modulator for event encoding, IEEE Journal of Solid-State Circuits, 50:(9), 2015.
S-C. Liu, M-H. Yang, A. Steiner, R. Moeckel, and, T. Delbruck, 1kHz 2D visual motion sensor using 20x20 silicon retina optical sensor and DSP microcontroller, IEEE Transactions on Biomedical Circuits and Systems, 2015.
C-H. Chien, S-C. Liu, and A. Steimer, A neuromorphic VLSI circuit for spike-based random sampling, IEEE Transactions on Emerging Topics in Computing: Special Issue on Advances in Neuromorphic and Analog VLSI Computing, 2015.
S. Bhargava, F. Blaettler, S. Kollmorgen, S-C. Liu, and R. H. Hahnloser, Linear methods for efficient and fast separation of two sources recorded with a single microphone, Neural Computation, 22(10), 2015
T. Delbruck, M. Pfeiffer, R. Juston, G. Orchard, E. Müggler, A. Linares-Barranco, and M.W. Tilden, Human vs computer slot car racing using an event and frame-based vision sensor, 2015 IEEE International Symposium on Circuits and Systems, 2015.
D. Moeys, S-C. Liu, and T. Delbruck, Current-mode automated quality control cochlear resonator for bird identity tagging, 2015 IEEE International Symposium on Circuits and Systems, 2015.
P. Klein, J. Conradt, and S-C. Liu, Scene stitching with event-driven sensors on a robot head platform, 2015 IEEE International Symposium on Circuits and Systems, 2015.
H. Liu, C. Brandli, C. Li, S-C. Liu, and T. Delbruck, Design of spatiotemporal correlation filter for event-based sensors, 2015 IEEE International Symposium on Circuits and Systems, 2015.
C. Li, C. Brandli, R. Berner, H. Liu, MH. Yang, S-C. Liu, and T. Delbruck, Design of an RGBW color VGA global-shutter static and dynamic vision sensor, 2015 IEEE International Symposium on Circuits and Systems, 2015.
S. Hussain, S-C. Liu, and A. Basu, Hardware-amenable structural learning for spike-based pattern classification using a simple model of active dendrites, Neural Computation, 27(4), pp. 845-897, 2015.

2014

C. Braendli, R. Berner, M-H. Yang, S-C. Liu, V. Villeneuva, and T. Delbruck, The ”DAVIS” dynamic and active-pixel vision sensor, 2014 IEEE International Symposium on Circuits and Systems, 2014.
C. Brandli, T. Mantel, M. Hutter, M. Hopflinger, R. Berner, R. Siegwart, and T. Delbruck Adaptive pulsed laser line extraction for terrain reconstruction using a Dynamic Vision Sensor, Frontiers in Neuromorphic Engineering, 2014.
D. Neil and S-C. Liu, Minitaur, an event-driven FPGA-Based spiking network accelerator, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, PP:(99) 1, 2014.
S. Hussain, S-C. Liu, S-C. and A. Basu, Improved margin multi-class classification using dendritic neurons with morphological learning, 2014 IEEE International Symposium on Circuits and Systems, 2014.
M. Lang and T. Delbruck Robotic goalie with 3ms reaction time at 4% CPU load using event-based Dynamic Sensor, Frontiers in Neuromorphic Engineering, 2014
A. Steiner, R. Moeckel, R. Thurer, D. Floreano, T. Delbruck, and S-C. Liu, 1kHz 2D silicon retina motion sensor platform, 2014 IEEE International Symposium on Circuits and Systems, 2014.
M-H. Yang, S-C. Liu, and T. Delbruck, Comparison of spike encoding schemes in asynchronous vision sensors: Modeling and design, 2014 IEEE International Symposium on Circuits and Systems, 2014.
M-H. Yang, S-C. Liu, and T. Delbruck, Subthreshold DC-gain enhancement by exploiting small size effects of MOSFETs, Electronics Letters, Vol. 50, (11), pp. 835 – 837, 2014.
J-H. Lee, T. Delbruck, M. Pfeiffer, P. K.J. Park, C-W. Shin, H. Ryu, and B. C. Kang. Real-time gesture interface based on event-driven processing from stereo silicon retinas, IEEE Transactions on Neural Networks and Learning Systems 1-14, 2014.

2013

S.-C. Liu, A. van Schaik, B. Minch, and T. Delbruck, Asynchronous binaural spatial audition sensor with 2x64x4 channel output, IEEE Transactions on Biomedical Circuits and Systems, 2013.
P. O'Connor, D. Neil, S.-C. Liu, T. Delbruck, and M. Pfeiffer, Real-time classification and sensor fusion with a spiking Deep Belief Network, Frontiers of Neuromorphic Engineering, 2013.
Y. Wang and S.-C. Liu, Active processing of spatio-temporal input patterns in silicon dendrites, IEEE Transactions on Biomedical Circuits and Systems, 7 (3), pp. 307-318, 2013.
R. Berner, C. Brandli, M. Yang, S.-C. Liu, and T. Delbruck, A 240×180 120dB 10mW 12μs-latency sparse output vision sensor for mobile applications, Proceedings of the 2013 International Image Sensor Workshop, pp. 41-44, 2013. (IISW slides)
R. Berner, C. Brandli, M. Yang, S.-C. Liu, and T. Delbruck, A 240×180 120dB 10mW 12μs-latency sparse output vision sensor for mobile applications, IEEE VLSI Symposium, pp. 186-187, 2013.
S. Hussain, R. Gopalakrishnan, A. Basu, and S-C. Liu, A morphological learning: Increased memory capacity of neuromorphic systems with binary synapses exploiting AER based reconfiguration, 2013 International Joint Conference on Neural Networks, 2013.
P. Park, H. Ryu, J. H. Lee, C. W. Shin, K. B. Lee, J. Y. Woo, J-S. Kim, B. C. Kang, S-C. Liu, and T. Delbruck, Fast neuromorphic sound localization for binaural hearing aids, IEEE Engineering in Medicine and Biology Society, 2013.

2012

T. Sejnowski and T. Delbruck, The language of the brain,Scientific American, vol. 307, no. 4, pp. 54-59, 2012.
M. Yang, S-C. Liu, C. Li, and T. Delbruck, Addressable current reference array with 170dB dynamic range, IEEE ISCAS, May 2012.
C. Li, T. Delbruck, and S-C. Liu, Real-time speaker identification using the AEREAR2 event-based silicon cochlea, IEEE ISCAS, May 2012.
J. Lee, T. Delbruck, P. Park, M. Pfeiffer, C.-W. Shin, H. Ryu, and B.-C Kang, Live Demonstration: Gesture-Based Remote Control using Stereo Pair of Dynamic Vision Sensors, IEEE ISCAS, May 2012 (Winner of Best Live Demonstration Award)
M. L. Katz, K. Nikolic, and T. Delbruck, Live demonstration: Behavioural emulation of event-based vision sensors, IEEE ISCAS, May, 2012.
M. Slaney, T. Agus, S.-C. Liu, M. Kaya, and M. Elhilali, A model of attention-driven scene analysis, IEEE ICASSP, March 2012.

2011

R. Berner and T. Delbruck, Event-Based Pixel Sensitive to Changes of Color and Brightness, IEEE TCAS-I, Vol. 58, 1581-1590, July 2011.
D. Drazen, P. Lichtsteiner, P. Hafliger, T. Delbruck, and A. Jensen, Toward Real-Time Particle Tracking using an Event-Based Dynamic Vision Sensor, Experiments in Fluids, Vol. 51, 1465-1469, 2011.
Y. Wang, S-C. Liu, A Two-Dimensional Configurable Active Silicon Dendritic Neuron Array, IEEE TCAS-I, Vol. 58, 2159-2171, 2011.
Y. Wang and S-C. Liu, Mismatch reduction through dendritic nonlinearities in a 2D silicon dendritic neuron array, IEEE ISCAS, May, 2011.
H. Finger and S-C. Liu, Estimating the Location of a Sound Source with a Spike-Timing Localization Algorithm, IEEE ISCAS, May, 2011.
M. Abdollahi and S-C. Liu, Speaker-Independent Isolated Digit Recognition using an AER Silicon Cochlea, IEEE BioCAS, November, 2011.
G. Indiveri et al., Neuromorphic Silicon Neuron Circuits, Frontiers in Neuromorphic Engineering, Vol. 5, 2011.
T. Delbruck et al., Confession Session: Learning from Others Mistakes, IEEE ISCAS, May, 2011.

2010

R. Berner, T. Delbruck, Event-based color change pixel in standard CMOS, IEEE ISCAS, May, 2010 (Best Student Paper, Best Sensory System Paper)
T. Delbruck, R. Berner, P. Lichtsteiner, C. Dualibe, 32-bit configurable bias current generator with sub-off-current capability, IEEE ISCAS, May, 2010
T. Delbruck, T. Koch, R. Berner, H. Hermansky, Fully integrated 500uW speech detection wake-up circuit, IEEE ISCAS, May, 2010
H. Finger, P. Ruvolo, S.-C. Liu, J. R. Movellan, Approaches and databases for online calibration of binaural sound localization for robotic heads, IEEE/RSJ IROS, Octorber, 2010
D. Jaeckel, R. Moeckel, S. -C. Liu, Sound recognition with spiking silicon cochlea and hidden Markov models, PRIME, 2010
S.-C. Liu, T. Delbruck, Neuromorphic sensory systems, Current Opinion in Neurobiology, Vol. 20, 288-295, 2010
S.-C. Liu, N. Mesgarani, J. Harris, H. Hermansky, The use of spike-based representations for hardware audition systems, IEEE ISCAS, May, 2010
S.-C. Liu, A. van Schaik, B. A. Minch, T. Delbruck, Event-based 64-channel binaural silicon cochlea with Q enhancement mechanisms, IEEE ISCAS, May, 2010
T. Delbruck, R. Berner, Temporal contrast AER pixel with 0.3%-contrast event threshold, IEEE ISCAS, May, 2010
T. Delbruck, B. Linares-Barranco, E. Culurciello, C. Posch, Activity-driven, event-based vision sensors, IEEE ISCAS, May, 2010