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Test-Time Data Augmentation
Tutorial on how to properly implement test-time image data augmentation in a production environment with limited computational resources.
data-augmentation keras production tensorflow
Neural Nets Aren’t Black Boxes
If you think neural nets are black boxes, you’re not alone. Let’s break this misconception down piece by piece as we build our own neural net from scratch.
deep-learning code article tutorial
A Few Favorite Recipes in Computer Vision & Deep Learning
This blog post enlists a few of my favorite recipes in deep learning in the context of computer vision (as of August 2020).
self-supervised-learning simclr contrastive-learning representation-learning
Nearest Celebrity Face
Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours. The input ...
deep-learning siamese-networks computer-vision code
Training CNN with Mixed Precision in PyTorch 1.6
Simple Example on MNIST dataset illustrating Mixed Precision Training.
deep-learning pytorch code tutorial
Extension to block NSFW content using AI
NSFW Filter is an extension that blocks NSFW content from your browser. It uses a computer vision model to detect NSFW content and hides it from the user.
machine-learning computer-vision tensorflow tensorflow-js
Deep Learning Techniques for NLP in Healthcare
A talk discussing the recent advancements of deep learning to facilitate the adaption of NLP in the healthcare domain.
health natural-language-processing deep-learning tutorial
Deep Learning's Most Important Ideas - A Brief Historical Review
Review well-adopted deep learning ideas that have stood the test of time.
deep-learning history article
Cartoonize your world!
A demo web application to showcase the capability of "white box cartoonization" on image and videos.
gans cartoon demo deep-learning
Understanding the Effectivity of Ensembles in Deep Learning
The report explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective by Stanislav Fort, Huiyi Hu, and Balaji Lakshminarayanan.
computer-vision deep-learning neural-networks ensembles
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