Reference implementation for Blueprint Separable Convolutions (CVPR 2020)

Keras w/ Tensorflow backend implementation for 3D channel-wise convolutions

Sound event detection with depthwise separable and dilated convolutions.

Online learning platform with automatic engagement recognition

Cheng-Hao Tu, Jia-Hong Lee, Yi-Ming Chan and Chu-Song Chen, "Pruning Depthwise Separable Convolutions for MobileNet Compression," International Joint Conference on Neural Networks, IJCNN 2020, July 2020.

Code for "Complex-Valued Depthwise Separable Convolutional Neural Network for Automatic Modulation Classification"

Xception V1 model in Tensorflow with pretrained weights on ImageNet

PyTorch implementation of Depthwise Separable Convolution

Project crafted by Antonio Ferrigno, Giulia Di Fede and Vittorio Di Giorgio for the Advanced Machine Learning course at Politecnico di Torino (2023/2024)

Neural Network for Low Complexity Acoustic Scene Classification

This repository contains research on real-time domain adaptation in semantic segmentation, aiming at bridging the gap between synthetic and real-world imagery for urban scenes and autonomous driving, utilizing STDC models and advanced domain adaptation methods.