InvokerLiu

InvokerLiu

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DenseNet-Tensorflow

a tensorflow implementation of DenseNet

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awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

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ConvNetDraw

Draw multi-layer neural network in your browser

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DANet

Dual Attention Network for Scene Segmentation (CVPR2019)

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DCCM

Deep Comprehensive Correlation Mining

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DeepFaceLab

DeepFaceLab is a tool that utilizes deep learning to recognize and swap faces in pictures and videos. Includes prebuilt ready to work standalone Windows 7,8,10 binary (look readme.md).

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DenseNet-1

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

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DenseNet-Keras

DenseNet Implementation in Keras with ImageNet Pretrained Models

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Depix

Recovers passwords from pixelized screenshots

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download

Lantern官方版本下载 蓝灯 翻墙 科学上网 外网 加速器 梯子 路由

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GIS-Info.github.io

GIS海外留学信息

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GNNPapers

Must-read papers on graph neural networks (GNN)

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ImageSegmentation

multiresolution segmentation for remote sensing images with thematic layer constraining

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keras-semantic-segmentation-example

Example of semantic segmentation in Keras

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KMeansForLargeImage

KMeans Cluster Algorithm for Large Image

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mmdetection

OpenMMLab Detection Toolbox and Benchmark

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models

Models and examples built with TensorFlow

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PCATransformationForLargeImage

Principal Components Analysis (PCA) Transformation for Large Image

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segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

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segnet.tf

SegNet-like Autoencoders in TensorFlow

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Tensorflow-Cookbook

Simple Tensorflow Cookbook for easy-to-use

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tensorflow-deeplab-resnet

DeepLab-ResNet rebuilt in TensorFlow

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tensorflow-fcn

An Implementation of Fully Convolutional Networks in Tensorflow.

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tensorflow-yolov3

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

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tf_unet

Generic U-Net Tensorflow implementation for image segmentation

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transformer

A TensorFlow Implementation of the Transformer: Attention Is All You Need

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