人工智能论文集锦

0 写在前面

体悟:

  • 从事人工智能行业,学术界产论文,工业界出产品.
  • 工业应用上应用技术,能将GitHub的算法"跑通",能训练,能调参,或复现论文算法即可完成产品转化的第一步;
  • 工程人员若想深入理解算法并进一步优化,则需要研究代码复现的论文,研究解决问题的原理及思路,这也是整理论文的意义所在;
  • 当然,研究论文与"跑通"代码先后顺序依据个人或公司需求,若需要快速演示成果,则先跑通代码,若不急于展示,则先研读论文,再复盘代码;
  • 做好笔记,可以是博客,在线文档,云盘等;
  • 时间是检验真理的标准,实践也是检验真理的标准;

1 计算机视觉理论篇

二位大神佳作:

  • 各种论文及GitHub
    https://handong1587.github.io/deep_learning/2015/10/09/dl-applications.html

  • 引入上面的杰作
    https://cloud.tencent.com/developer/article/1162172

1.0 VGGNet

  • Paper传送门
    Very Deep Convolutional Networks for Large-sacle Image Recognition

2 计算机视觉应用篇

2.0 图像风格转换

  • "原始"方法Paper传送门
    A Neural Algorithm of Artistic Style
  • "快速"方法Paper传送门
    Perceptual Losses for Real-Time Style Transfer and Super-Resolution
  • 人脸转换Nvidia
    A Style-Based Generator Architecture for Generative Adversarial Networks

2.1 图像修复

  • Paper传送门
    Context Encoders: Feature Learning by Inpainting
  • Paper传送门
    High-Resolution Image Inpainting using Multi-Scale Neural Patch Systhesis

2.2 人脸识别

  • DCNN Face++
    Deep Convolutional Network Cascade for Facial Point Detection

2.2 图像检测

  • YOLO
    You Only Look Once:Unified, Real-Time Object Detection
  • MR-CNN
    Object detection via a multi-region & semantic segmentation-aware CNN model
  • Cascade R-CNN
    Cascade R-CNN: Delving into High Quality Object Detection

2.3 视频实时目标检测

  • Faster R-CNN
    Faster R-CNN: Towards Real-Time Object
    Detection with Region Proposal Networks
  • R-FCN
    R-FCN: Object Detection via Region-based Fully Convolutional Networks
  • SSD
    SSD: Single Shot MultiBox Detector
  • Mobile Devices
    Pelee: A Real-Time Object Detection System on Mobile Devices
  • T-CNN
    Quantization Mimic: Towards Very Tiny CNN for Object Detection

3 自然语言处理

3.1 句子分类池化

  • 句子建模
    A Convolutional Neural Network for Modelling Sentences
  • 句子分类
    A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification
  • 句子分类
    Convolutional Neural Networks for Sentence Classification

3.2 翻译

  • Transforer模型
    Attention Is All You Need
  • GLUE
    GLUE: A Multi-Task Benchmark and Analysis Platform for Natural LanguageUnderstanding
  • seqence2sequence
    Sequence to Sequence Learning with Neural Networks

3.3 音乐识别

An Industrial-Strength Audio Search Algorithm

4 总结

  • 多看论文,多写代码;
  • 有坑,慢慢填;
  • 戒骄戒躁;
  • 相信时间,相信实践;

[参考文献]
[1]https://blog.csdn.net/yhl_leo/article/details/56674833
[2]https://cloud.tencent.com/developer/article/1162172
[3]https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html#yolo


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