Abstract
In this paper, three alternative VLSI analog implementations of CNNs are described, which have been devised to perform image processing and vision tasks: a programmable low-power CNN with embedded photosensors, a compact fixed-template CNN based on unipolar current-mode signals, and basic CMOS circuits to implement an extended CNN model using spikes. The first two VLSI approaches are intended for focal-plane image processing applications. The third one allows, since its dynamics is defined by process-independent local ratios and its input/outputs can be efficiently multiplexed in time, the construction of very large multiple chip CNNs for more complex vision tasks.
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Anguita, M., Pelayo, F.J., Ros, E., Palomar, D., Prieto, A. (1998). Focal-Plane and Multiple Chip VLSI Approaches to CNNs. In: Chua, L.O., Gulak, G., Pierzchala, E., Rodríguez-Vázquez, A. (eds) Cellular Neural Networks and Analog VLSI. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4730-0_4
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