lrtacss's Stars
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
DingXiaoH/RepVGG
RepVGG: Making VGG-style ConvNets Great Again
Jongchan/attention-module
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
bubbliiiing/yolov5-pytorch
这是一个YoloV5-pytorch的源码,可以用于训练自己的模型。
bubbliiiing/yolox-pytorch
这是一个yolox-pytorch的源码,可以用于训练自己的模型。
bubbliiiing/mobilenet-yolov4-pytorch
这是一个mobilenet-yolov4的库,把yolov4主干网络修改成了mobilenet,修改了Panet的卷积组成,使参数量大幅度缩小。
mohenghui/detectAuto
自动标注
MRSRL/complex-networks-release
Implementation related to the paper "Analysis of deep complex-valued convolutional neural networks for MRI reconstruction and phase-focused applications" by Elizabeth K. Cole et. al; Toolbox for complex-valued convolution and activation functions using an unrolled architecture.
pheepa/DCUnet
Phase-aware speech enchancement with Deep Complex U-Net
Alien9427/SAR_specific_models
fudanxu/MSTAR-AConvNet
AConvNet on Caffe for [Chen et al. IEEE TGRS vol.54 no.8]
Alien9427/XAI4SAR-PGIL
The physics guided and injected learning NN for SAR image patch-wise classification
Jiankun-chen/CVCMFFNet-master
We present a novel complex-valued convolutional and multi-feature fusion network (CVCMFF Net) specifically for building semantic segmentation of InSAR images. It can effectively segment the layover, shadow, and background on both the simulated InSAR building images and the real airborne InSAR images. The segmentation performance of CVCMFF Net is significantly improved compared with other state-of-the-art networks. The comparative experiments are link to https://github.com/Jiankun-chen/building-semantic-segmentation-of-InSAR-images
xingyifei2016/RotLieNet