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advanced-java

😮 互联网 Java 工程师进阶知识完全扫盲：涵盖高并发、分布式、高可用、微服务、海量数据处理等领域知识，后端同学必看，前端同学也可学习

amazing-semantic-segmentation

Amazing Semantic Segmentation on Tensorflow && Keras (include FCN, UNet, SegNet, PSPNet, PAN, RefineNet, DeepLabV3, DeepLabV3+, DenseASPP, BiSegNet)

annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

architect-awesome

后端架构师技术图谱

attentiondeeplabv3p

Attention Deeplabv3+: Multi-level Context Attention Mechanism for Skin Lesion Segmentation

augmentor

Image augmentation library in Python for machine learning.

awesome-cv-attention

awesome-lane-detection

A paper list of lane detection.

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

awesome-trajectory-prediction

cbam.pytorch

Non-official implement of Paper：CBAM: Convolutional Block Attention Module

cs-notes

:books: 技术面试必备基础知识、Leetcode、Java、C++、Python、后端面试、计算机操作系统、计算机网络、系统设计

deeplabv3plus-pytorch-attention

demo-network

AlexNet，GoogleNet，VGG和ResNet网络架构的demo示例

densecrf

A lightweight MATLAB and Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.

javacore

learning notes of JavaCore

javacore-1

:coffee: JavaCore 是对 Java 核心技术的经验总结。

javacorevol1_notes

《Java 核心编程：卷一》笔记

javafamily

【互联网一线大厂面试+学习指南】进阶知识完全扫盲：涵盖高并发、分布式、高可用、微服务等领域知识，作者风格幽默，看起来津津有味，把学习当做一种乐趣，何乐而不为，后端同学必看，前端同学我保证你也看得懂，看不懂你加我微信骂我渣男就好了。

javaguide

【Java学习+面试指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。

labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

leetcodeanimation

Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）

models

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

multiyolov5

joint detection and semantic segmentation, based on ultralytics/yolov5,

paddlex-vehicle-detection-with-yolov3

（车辆检测和车道分割）vehicle detection and lane segmentation based on YOLOv3 with paddlex

py_img_seg_eval

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

pytorch-semseg

Semantic Segmentation Architectures Implemented in PyTorch

segment_indicator

code of segment indicator

semantic-segmentation

Classified & clustered every pixel in cityscape dataset image belonging to same object class in modified Google DeepLabV3 architecture. Enhanced boundary detection of the Image Net (ResNet) with atrous conv & Atrous Spatial Pyramid Pooling (ASPP) with variable dilation rates by using end to end Holistic Edge Detection(HED) technique. Added Squeeze & Excitation (SE) block to improve channel attention & also tested softmax in stead of sigmoid for last layer of SE.

semantic-segmentation-pytorch

Semantic segmentation models implemented in PyTorch