FPGA Implementation for Odor Identification with Depthwise Separable Convolutional Neural Network.

The integrated electronic nose (e-nose) design, which integrates sensor arrays and recognition algorithms, has been widely used in different fields. However, the current integrated e-nose system usually suffers from the problem of low accuracy with simple algorithm structure and slow speed with complex algorithm structure. In this article, we propose a method for implementing a deep neural network for odor identification in a small-scale Field-Programmable Gate Array (FPGA).

An Odor Labeling Convolutional Encoder-Decoder for Odor Sensing in Machine Olfaction.

Deep learning methods have been widely applied to visual and acoustic technology. In this paper, we propose an odor labeling convolutional encoder-decoder (OLCE) for odor identification in machine olfaction. OLCE composes a convolutional neural network encoder and decoder where the encoder output is constrained to odor labels.