Popular GitHub Repositories for Oversampling Technique

Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun

A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.

A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun

A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and?code

[ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.

Synthetic Minority Over-Sampling Technique for Regression

Dataset and code of GTSinger(NeurIPS 2024 Spotlight): A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks

A generalized gradient-based CNN visualization technique

? PyTorch based visualization package for generating layer-wise explanations for CNNs.

PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.

This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.

This code extends the neural style transfer image processing technique to video by generating smooth transitions between several reference style images

Elastic weight consolidation technique for incremental learning.

A curated list of the top 10 computer vision papers in 2021 with video demos, articles, code and paper reference.

Object Detection on Radar sensor and RGB camera images. https://ieeexplore.ieee.org/document/9191046 Full Thesis : RADAR+RGB Fusion for Robust Object Detection in Autonomous Vehicles. Zenodo. https://doi.org/10.5281/zenodo.13738235

Instantly improve your training performance of TensorFlow models with just 2 lines of code!

We propose a simple yet efficient technique to leverage semantic segmentation model to extract and separate individual buildings in densely compacted areas using medium resolution satellite/UAV orthoimages. We adopted standard UNET architecture, additionally added batch normalization layer after every convolution, to label every pixel in the image.

Tensorflow Advanced Technique Specialization

[SOTA] [92% acc] 786M-8k-44L-32H multi-instrumental music transformer with true full MIDI instruments range, efficient encoding, octo-velocity and outro tokens

klmbr - a prompt pre-processing technique to break through the barrier of entropy while generating text with LLMs