Mihaela Grigore
  • 👋About
  • 👩‍🏭Personal projects
    • Computer Vision | Deep Learning with Tensorflow & Keras (ResNet50, GPU training)
    • Computer Vision | Convolutional Neural Networks with PyTorch
    • Computer Vision | Facial Recognition with Keras, FaceNet, Inception, Siamese Networks
    • NLP | Topic modeling on tweets
    • NLP | Sentiment analysis of tweets: TextBlob, VADER and Flair
    • Time series | Exploration on Crypto price dataset
    • Data scraping | Social Media Scraping: Twitter Developer API for Academics
    • Data Scraping | Collecting historical tweets without Twitter API
  • ✍️Notes
    • Machine Learning in Production
      • Feature transforms
      • Feature selection
      • Data journey
    • NLP
      • Information Retrieval
    • Computer Vision
    • Time series
      • Stationarity
    • Data
      • Labeling
    • Python
      • ndarray slicing with index out of bounds
  • 📚Readings & other media
    • Computer Vision
      • Selection of research articles
    • NLP
      • Handwriting Text
      • Information Retrieval
      • Mono- / multilingual
      • Topic Modeling
      • Language Models
    • Time Series
    • Generative Adversarial Netoworks (GAN)
    • Python
      • Python basics
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  1. Readings & other media
  2. Computer Vision

Selection of research articles

These are some of the best resources for aquiring basic knowledge, which I came across while working on Computer Vision

What
Type
Author(s)
Link

Good overview of image segmentation research and algorithms

blog post

some company

https://nanonets.com/blog/semantic-image-segmentation-2020/

Stanford CS231n

course

Fei Fei Lin

http://cs231n.stanford.edu/slides/

Fully Convolutional Networks for Semantic Segmentation

paper

never heard of

https://arxiv.org/abs/1411.4038

U-Net: Convolutional Networks for Biomedical Image Segmentation

paper

never heard of

https://arxiv.org/abs/1505.04597

understand convolution layer

video

Andrew Ng

https://www.youtube.com/watch?v=jPOAS7uCODQ&ab_channel=DeepLearningAI

A cleaner explanation of main points from the FCN paper

blog post

some Phd student (Sik-Ho Tsang)

https://towardsdatascience.com/review-fcn-semantic-segmentation-eb8c9b50d2d1

Sik-Ho Tsang - reading list

list of important topics in Computer Vision and link to papers

Sik-Ho Tsang

https://sh-tsang.medium.com/overview-my-reviewed-paper-lists-tutorials-946ce59fbf9e

list of Medium articles where he reviews papers

Sik-Ho Tsang

https://sh-tsang.medium.com/

all you need to know about convolutional layers

blog post

Machine learning mastery

https://machinelearningmastery.com/convolutional-layers-for-deep-learning-neural-networks/

very good intuitive explanation of upsampling through transposed convolutions

blog post

some company

https://medium.com/apache-mxnet/transposed-convolutions-explained-with-ms-excel-52d13030c7e8

A guide to convolution arithmetic for deep learning

book(let)

researchers

https://arxiv.org/pdf/1603.07285.pdf

good overview of computer vision tasks

blog post

https://towardsdatascience.com/understanding-semantic-segmentation-with-unet-6be4f42d4b47

compute conv layers output size (regular, transposed, stride, padding)

blog post

http://makeyourownneuralnetwork.blogspot.com/2020/02/calculating-output-size-of-convolutions.html

AI GIS library

library website with documentation and AI models and methods explained

https://developers.arcgis.com/python/guide/how-unet-works/

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Last updated 3 years ago

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