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Cheng Wang's Projects

3dunetcnn icon 3dunetcnn

Keras 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation

dhash icon dhash

基于感知哈希的图像相似度检测

fcn.tensorflow icon fcn.tensorflow

Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)

intelligent-traffic-based-on-cv icon intelligent-traffic-based-on-cv

本项目为2020年**软件杯A组第一批赛题"基于计算机视觉的交通场景智能应用".项目用python实现,主要使用YOLO模型实现道路目标如人、车、交通灯等物体的识别,使用开源的"中文车牌识别HyperLPR"项目实现车牌识别功能.

keras-yolo3 icon keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)

mri-u-net icon mri-u-net

基于U-net和MRI图像的膀胱壁边缘以及膀胱肿瘤检测

py_img_seg_eval icon py_img_seg_eval

Evaluation metrics for image segmentation inspired by paper Fully Convolutional Networks for Semantic Segmentation

pytorch_classification icon pytorch_classification

利用pytorch实现图像分类的一个完整的代码,训练,预测,TTA,模型融合,模型部署,cnn提取特征,svm或者随机森林等进行分类,模型蒸馏,一个完整的代码

rcnn-results-gui icon rcnn-results-gui

GUI to show results of detection using py-faster-rcnn on pictures, the results must have been converted to XML format

tensorflow-serving-yolov3 icon tensorflow-serving-yolov3

本项目主要对原tensorflow-yolov3版本做了许多细节上的改进,增加了TensorFlow-Serving工程部署,训练了多个数据集,包括Visdrone2019, 安全帽等, 安全帽mAP在98%左右, 推理速度1080上608的尺寸大概25fps.

tensorflow-yolov3 icon tensorflow-yolov3

🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset

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