monchhichizzq

monchhichizzq

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Unet_Medical_Segmentation

This is an implementation of “U-Net: Convolutional Networks for Biomedical Image Segmentation” and "UNet++: A Nested U-Net Architecture for Medical Image Segmentation" in Python and powered by the Tensorflow2 deep learning framework. Unet family has been proposed for a more precise segmentation on medical image.

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tensorflow2-yolov5

YoloV5 implemented by TensorFlow2 , with support for training, evaluation and inference.

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DeepLabV3_plus

DeepLabV3+ is a state-of-art deep learning model for semantic image segmentation.

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Tensorflow2-yolov4

YoloV4 implemented by TensorFlow2 , with support for training, evaluation and inference.

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Mobilenet-SSD-Kitti-Object-Detection

Mobilenet-SSD-Kitti-Object-Detection

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CenterNet

CenterNet for object detection

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google-research

Google Research

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keras

Deep Learning for humans

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loss_summary

A simple summary of loss functions in machine learning

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MobileNet-summary-Z

MobileNet is a mobile classification network proposed by Google

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Model_Prunning

Several basic methods for model compression

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Model_Quantization

The basic methods for model quantization

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movenet_pytorch

A Pytorch implementation of MoveNet from Google. Include training code and pre-trained model.

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pip_tutorial

This is a simple example package.

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Semantic_Segmentation

Image segmentation refers to dividing an image into several disjoint regions based on features such as grayscale, color, spatial texture, geometric shape, etc., so that these features show consistency or similarity within the same region, while showing significant differences between different regions

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StreamYOLO

Real-time Object Detection for Streaming Perception, CVPR 2022

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Tensorflow2-HRNet

HRNet implemented by TensorFlow2 , with support for training, evaluation and inference.

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