LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation
ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation
lightweight and efficient cnn for semantic segmentation, my blog address:
Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)
Record some tools commonly used in research, My blog address:
Welcome to my blog address:
:books: 技术面试需要掌握的基础知识
AI算法岗求职攻略(涵盖准备攻略、刷题指南、内推和AI公司清单等资料)
中文 Python 笔记
关注未来热门新技术:AI(人工智能)/IoT(物联网)/IoV(车联网)/AR(增强现实)/VR(虚拟现实)/MR(混合现实)/Deep Learning(深度学习)/Big Data(大数据)/Self Driving(自动驾驶)/3D Printing(3D 打印)/UAV(无人机)/Robot(机器人)/Block Chain(区块链)/Maker(创客)
Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models
💎 一款超轻量级通用人脸检测模型(模型文件大小仅1MB,320x240输入下计算量仅90MFlops)适用于边缘计算设备、移动端设备以及PC
An open source library for face detection in images. The face detection speed can reach 1500FPS.
High-resolution representation learning (HRNets) for Semantic Segmentation
We achieve SOTA on 6 different semantic segmentation benchmarks
A PyTorch-Based Framework for Deep Learning in Computer Vision
深度学习工程师生存指南
NIPS poster latex template (with bandit framework on top of Reinforcement Learning agents example)
Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.
Pyramid Stereo Matching Network (CVPR2018)
程序员如何申请到澳洲工作
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OpenEdge ABL | 4 | 98.49% | 60 |
Python | 767 | 99.16% | 357 |
Jupyter Notebook | 2484 | 80.36% | 1 |
HTML | 6304 | 89.80% | 2 |