4 papers
BILLNET: A Binarized Conv3D-LSTM Network with Logic-gated residual architecture for hardware-efficient video inference
Van Thien Nguyen, William Guicquero, Gilles Sicard
Long Short-Term Memory (LSTM) and 3D convolution (Conv3D) show impressive results for many video-based applications but require large memory and intensive computing. Motivated by r…
MOGNET: A Mux-residual quantized Network leveraging Online-Generated weights
Van Thien Nguyen, William Guicquero, Gilles Sicard
This paper presents a compact model architecture called MOGNET, compatible with a resource-limited hardware. MOGNET uses a streamlined Convolutional factorization block based on a…
A 1Mb mixed-precision quantized encoder for image classification and patch-based compression
Van Thien Nguyen, William Guicquero, Gilles Sicard
Even if Application-Specific Integrated Circuits (ASIC) have proven to be a relevant choice for integrating inference at the edge, they are often limited in terms of applicability.…
Histogram-Equalized Quantization for logic-gated Residual Neural Networks
Van Thien Nguyen, William Guicquero, Gilles Sicard
Adjusting the quantization according to the data or to the model loss seems mandatory to enable a high accuracy in the context of quantized neural networks. This work presents Hist…