Scene Context Classification with Event-Driven Spiking Deep Neural Networks
Event-Driven computation is attracting growing attention among researchers for several reasons. On one hand, the availability of new bio-inspired retina-like vision sensors that provide spiking outputs, like the Dynamic Vision Sensor (DVS) make it possible to demonstrate energy efficient and high-sp...
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| Otros Autores: | , , |
| Formato: | Acta de conferencia Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
Institute of Electrical and Electronics Engineers Inc.
2019
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| Acceso en línea: | Registro en Scopus DOI Handle Registro en la Biblioteca Digital |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 06174caa a22006497a 4500 | ||
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| 001 | PAPER-25755 | ||
| 003 | AR-BaUEN | ||
| 005 | 20230518205752.0 | ||
| 008 | 190410s2019 xx ||||fo|||| 10| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-85062300105 | |
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 100 | 1 | |a Negri, P. | |
| 245 | 1 | 0 | |a Scene Context Classification with Event-Driven Spiking Deep Neural Networks |
| 260 | |b Institute of Electrical and Electronics Engineers Inc. |c 2019 | ||
| 506 | |2 openaire |e Política editorial | ||
| 504 | |a Szummer, M., Picard, R.W., Indoor-outdoor image classification (1998) International Workshop on Content-Based Access of Image and Video Database, pp. 42-51. , Jan | ||
| 504 | |a Lichtsteiner, P., Posch, C., Delbruck, T., A 128128 120db 15us latency asynchronous temporal contrast vision sensor (2008) JSSC, 43 (2), pp. 566-576 | ||
| 504 | |a Posch, C., Matolin, D., Wohlgenannt, R., A qvga 143 db dynamic range frame-free PWM image sensor with lossless pixel-level video compression and time-domain cds (2011) IEEE J. of Solid-State Circ, 46 (1), pp. 259-275. , Jan | ||
| 504 | |a Serrano-Gotarredona, T., Linares-Barranco, B., A 128x128 1. 5sensitivity 0. 9sensor using transimpedance preamplifiers (2013) IEEE Journal of Solid-State Circuits, 48 (3), pp. 827-838 | ||
| 504 | |a Guo, M., Huang, J., Chen, S., Live demonstration: A 768-640 pixels 200meps dynamic vision sensor (2017) 2017 IEEE International Symposium on Circuits and Systems (ISCAS), p. 1. , May | ||
| 504 | |a Son, B., Suh, Y., Kim, S., Jung, H., Kim, J.S., Shin, C., Park, K., Ryu, H., 4. 1 a 640x480 dynamic vision sensor with a 9um pixel and 300meps address-event representation (2017) 2017 IEEE International Solid-State Circuits Conference (ISSCC), pp. 66-67. , Feb | ||
| 504 | |a Pérez-Carrasco, J., Mapping from frame-driven to frame-free event-driven vision systems by low-rate rate coding and coincidence processing-application to feedforward convnets (2013) PAMI, 35 (11), pp. 2706-2719 | ||
| 504 | |a Lungu, I.A., Corradi, F., Delbrck, T., Live demonstration: Convolutional neural network driven by dynamic vision sensor playing roshambo (2017) 2017 IEEE International Symposium on Circuits and Systems (ISCAS), , May | ||
| 504 | |a (2018) MegaSim, , https://bitbucket.org/bernabelinares/megasim | ||
| 504 | |a Sivilotti, M., (1991) Wiring Considerations in Analog VLSI Systems with Application to Field-programmable Networks, , PhD, Computation and Neural Systems, Caltech, Pasadena California | ||
| 504 | |a Stromatias, E., Soto, M., Serrano-Gotarredona, T., Linares-Barranco, B., An event-driven classifier for spiking neural networks fed with synthetic or dynamic vision sensor data (2017) Frontiers in Neuroscience, 11, p. 350 | ||
| 504 | |a Bottou, L., Large-scale machine learning with stochastic gradient descent (2010) International Conference on Computational Statistics, pp. 177-187. , Physica-Verlag HD | ||
| 520 | 3 | |a Event-Driven computation is attracting growing attention among researchers for several reasons. On one hand, the availability of new bio-inspired retina-like vision sensors that provide spiking outputs, like the Dynamic Vision Sensor (DVS) make it possible to demonstrate energy efficient and high-speed complex vision tasks. On the other hand, the emergence of abundant new nanoscale devices that operate as tunable two-terminal resistive elements, which when operated through dynamic pulsing techniques emulate learning and processing in the brain, promise an explosion of highly compact energy efficient neuromorphic event-driven applications. In this paper we focus for the first time on a high-level cognitive task, namely scene context classification, performed by event-driven computations and using real sensory data from a DVS camera. © 2018 IEEE. |l eng | |
| 536 | |a Detalles de la financiación: TEC2015-63884-C2-1-P | ||
| 536 | |a Detalles de la financiación: European Regional Development Fund | ||
| 536 | |a Detalles de la financiación: H2020 Euratom, EURATOM, 644096 | ||
| 536 | |a Detalles de la financiación: 687299, NEURAM3 | ||
| 536 | |a Detalles de la financiación: ACKNOWLEDGMENTS This work was funded by EU H2020 grants 644096 (ECO-MODE) and 687299 (NEURAM3), and by Spanish grant from the Ministry of Economy and Competitivity TEC2015-63884-C2-1-P (COGNET) (with support from the European Regional Development Fund). | ||
| 593 | |a Instituto en Ciencias de la Computación (UBA-CONICET), Buenos Aires, Argentina | ||
| 593 | |a Instituto de Microelectrónica de Sevilla (IMSE-CNM), CSIC, Universidad de Sevilla, Sevilla, Spain | ||
| 690 | 1 | 0 | |a ENERGY EFFICIENCY |
| 690 | 1 | 0 | |a CONTEXT CLASSIFICATION |
| 690 | 1 | 0 | |a DYNAMIC VISION SENSORS |
| 690 | 1 | 0 | |a ENERGY EFFICIENT |
| 690 | 1 | 0 | |a EVENT DRIVEN APPLICATIONS |
| 690 | 1 | 0 | |a NANOSCALE DEVICE |
| 690 | 1 | 0 | |a PULSING TECHNIQUE |
| 690 | 1 | 0 | |a RESISTIVE ELEMENTS |
| 690 | 1 | 0 | |a VISION SENSORS |
| 690 | 1 | 0 | |a DEEP NEURAL NETWORKS |
| 700 | 1 | |a Soto, M. | |
| 700 | 1 | |a Linares-Barranco, B. | |
| 700 | 1 | |a Serrano-Gotarredona, T. | |
| 711 | 2 | |d 9 December 2018 through 12 December 2018 |g Código de la conferencia: 144481 | |
| 773 | 0 | |d Institute of Electrical and Electronics Engineers Inc., 2019 |h pp. 569-572 |p IEEE Int. Conf. Electron. Circuits Syst., ICECS |n 2018 25th IEEE International Conference on Electronics Circuits and Systems, ICECS 2018 |z 9781538695623 |t 25th IEEE International Conference on Electronics Circuits and Systems, ICECS 2018 | |
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| 856 | 4 | 0 | |u https://doi.org/10.1109/ICECS.2018.8617982 |y DOI |
| 856 | 4 | 0 | |u https://hdl.handle.net/20.500.12110/paper_97815386_v_n_p569_Negri |y Handle |
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