wdweqd's Stars
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
ultralytics/ultralytics
Ultralytics YOLO11 🚀
open-mmlab/mmdetection
OpenMMLab Detection Toolbox and Benchmark
WZMIAOMIAO/deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
WongKinYiu/yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
ultralytics/yolov3
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
THU-MIG/yolov10
YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]
meituan/YOLOv6
YOLOv6: a single-stage object detection framework dedicated to industrial applications.
Fafa-DL/Awesome-Backbones
Integrate deep learning models for image classification | Backbone learning/comparison/magic modification project
megvii-model/ShuffleNet-Series
YimianDai/open-aff
code and trained models for "Attentional Feature Fusion"
cv516Buaa/tph-yolov5
zhilin007/FFA-Net
FFA-Net: Feature Fusion Attention Network for Single Image Dehazing
VisDrone/DroneVehicle
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning
z1069614715/z1069614715
Liuchen1997/RFAConv
RAFConv: Innovating Spatital Attention and Standard Convolutional Operation
aaaaangel/RRDNet
Implementation of "Zero-Shot Restoration of Underexposed Images via Robust Retinex Decomposition, International Conference on Multimedia and Expo, 2020"
GhTara/Convolutional-Fuzzy-Neural-Network
Fuzzy-CNN comes to help improve the results of training on small data.
kangyuzhe666/yolov3_cam_frm
yolov3基础上添加cam与frm模块参考context_augmentation_and_featu
SonbolYb/Deep-Neuro-Fuzzy
cyborgoat/AOD-DC-Net
HuanBor/CBAM-AOD-Net
This is an improved AOD-Net defogging network based on the CBAM attention mechanism
Wei-JL/ACSTNet
ACSTNet: An improved YOLO X method for small object detection with pixel-level attention and parallel Swin Transformer
BernardTockmaji/Fuzzy-Logic-Image-Enhancement
Using Fuzzy Logic Algorithm
ighose/DeRaining-of-images
Trained a CNN to remove rain from images. Used Peak Signal to Noise Ratio as the loss function. This was done as part of Neural Networks and Fuzzy logic coursework.
A-Akhilesh/Improved-YoloV5-with-CBAM-C3TR-For-Small-Object-Detection-to-Detect-Floating-Bottles