Found 69 repositories(showing 30)
huggingface
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
jiaowoguanren0615
This is a warehouse for MobileNetV4-Pytorch-model, can be used to train your image-datasets for vision tasks.
jaiwei98
An unofficial implementation of MobileNetV4 in Pytorch
GuoquanPei
This is an improvement strategy based on YOLOv8, which uses MobileNetv4 to improve the model. It can reduce the parameters of the model and improve the model accuracy.
d-li14
PyTorch implementation of MobileNetV4 family
ChengpengChen
RepGhostNetV2: When RepGhost meets MobileNetV4
XuecenZhang-CWRU
No description available
junaidaliop
PyTorch replication of the MobileNetV4 Model
wh1090220084
No description available
liwer0715
将rtmpose的backbone替换为mobilenetv4
freedomtan
Profiling MobilenetV4 CoreML model
bit-admin
A PyTorch-based image classification system that trains a MobileNetV4 model to classify different types of slide presentations and screen states.
Leacius
No description available
wxhwxhwxh2002
Fatigue Driving Detection, YOLOv8 + MobileNetV4-Small + SimAM + WIoUv1
hunter20041220
MobileNetV4,SPD-Conv,RFAConv,NWD + Slide.Use them to improve yolov11 to make it light
Jingik
No description available
Ice-word
No description available
jpanagos
Straightforward implementation of MobileNetV4 https://arxiv.org/abs/2404.10518
Aabhash-19
PyTorch implementations of baseline and enhanced MobileNetV4 models on CIFAR-10. Features Apple Silicon GPU acceleration, advanced optimization techniques, and significant accuracy improvements.
No description available
Sindhuhurakadli
This project classifies breast cancer histopathology images using MobileNetV4, achieving 90.87% accuracy. It is lightweight, efficient, and deployable on edge devices, enabling real-time, resource-friendly cancer detection in low-resource settings.
20it091
I made an ML model using MobileNetv4 to distinguish between horses and humans
lollogiro
Benchmarking MobileNetV3 and MobileNetV4 on wildlife camera images for metereological image classification
CannotThinkOfAName
使用mobilenet v4实现图像检测
Taiheng119
CODE of A Lightweight MobileNetV4 Approach with ODConv and ASPP
alsgkals2
Simple codes for MobileNetv4
anysers
MobileNetV4架构解析与端侧部署实战
samrahasnain
No description available
sharika-2004
No description available
zayfitri
No description available