depthwise-separable-convolutions
There are 27 repositories under depthwise-separable-convolutions topic.
zeiss-microscopy/BSConv
Reference implementation for Blueprint Separable Convolutions (CVPR 2020)
alexandrosstergiou/keras-DepthwiseConv3D
Keras w/ Tensorflow backend implementation for 3D channel-wise convolutions
dr-costas/dnd-sed
Sound event detection with depthwise separable and dilated convolutions.
amrzhd/EEGNet
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
Amir-Hofo/EEGNet_Pytorch
This code implements the EEG Net deep learning model using PyTorch. The EEG Net model is based on the research paper titled "EEGNet: A Compact Convolutional Neural Network for EEG-based Brain-Computer Interfaces".
yogesh-kamat/EduMeet
Online learning platform with automatic engagement recognition
ivclab/Multistage_Pruning
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.
HiKapok/Xception_Tensorflow
Xception V1 model in Tensorflow with pretrained weights on ImageNet
tallamjr/astronet
Efficient Deep Learning for Real-time Classification of Astronomical Transients and Multivariate Time-series
Patrick-Nick/CDSCNN
Code for "Complex-Valued Depthwise Separable Convolutional Neural Network for Automatic Modulation Classification"
reshalfahsi/separableconv-torch
PyTorch implementation of Depthwise Separable Convolution
antonio-f/TF2_MobileNetV2_TransferLearning
MobileNet V2 transfer learning with TensorFlow 2.
claudiotancredi/Real-time-domain-adaptation-in-semantic-segmentation
"Advanced Machine Learning" project @ Politecnico di Torino, a.y. 2021/2022.
mr7495/image-classification-spatial
A novel architecture for enhancing image classification. Reference paper: https://arxiv.org/abs/2104.12294
naivomah3/lab-cv
Implementation of state-of-the-art models to do segmentation over our own dataset.
TanyaChutani/Xception-Tf2.0
A TensorFlow2.0 implementation of Xception Deep Learning with Depthwise Separable Convolutions
Jash-2000/Complex_Convolutional_Neural_Network_Architecture
I Implemented some of the custom complex Convolutional Neural Network architecture using tensorow.keras Functional API.
AhmedERady/Grad_Project
Smart Automation Controller for Precision Agriculture
ebuka-olisa/low-complexity-acoustic-scene
Neural Network for Low Complexity Acoustic Scene Classification
GiuDF1102/Real-time-Domain-Adaptation-in-Semantic-Segmentation
Project crafted by Antonio Ferrigno, Giulia Di Fede and Vittorio Di Giorgio for the Advanced Machine Learning course at Politecnico di Torino (2023/2024)
Aleedm/Real-time-Domain-Adaptation-in-Semantic-Segmentation
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.
LostOxygen/bioinf_kernel_eval
Performance Evaluation between Normal and Depthwise Seperable Convolutions for Medical Image Classification.
mohammad95labbaf/Lung-Segmentation
The preparation for the Lung X-Ray Mask Segmentation project included the use of augmentation methods like flipping to improve the dataset, along with measures to ensure data uniformity and quality. The model architecture was explored with two types of ResNets: the traditional CNN layers and Depthwise Separable.
anshul1004/MobileNet
Implementation and research paper of MobileNet
bensooraj/pytorch-s9-CIFAR10
Depthwise Separable Convolution and Albumentations
MU-PING/Depthwise-separable-CNN
Compare regular CNN with depthwise separable CNN for lightweight network
omarxadel/edgeml-project
Lightweight Attention U-Net for Breast Cancer Semantic Segmentation