There are 1 repository under data-augmentation-strategies topic.
[CVPR 2021] Code for "Augmentation Strategies for Learning with Noisy Labels".
Data Augmentation For Object Detection using Pytorch and PIL
The official implementation of ACL 2020, "Logic-Guided Data Augmentation and Regularization for Consistent Question Answering".
The source code and pre-trained models for Motion Matters: Neural Motion Transfer for Better Camera Physiological Sensing (WACV 2024, Oral).
Unofficial Pytorch Implementation Of AdversarialAutoAugment(ICLR2020)
Projet-PI-4DS2
[KDD23] Official PyTorch implementation for "Improving Conversational Recommendation Systems via Counterfactual Data Simulation".
[KDD23] Official PyTorch implementation for "Improving Conversational Recommendation Systems via Counterfactual Data Simulation".
Codes for employing PySimMIBCI for MI-EEG data generation and for using such data with FBCNetToolbox models
Extra bits of unsanitized code for plotting, training, etc. related to our CVPR 2021 paper "Augmentation Strategies for Learning with Noisy Labels".
A toolkit to augment audios (e.g. noise, reverb, distort, speedup, packet loss, farfield effects).
[ACL'2023 Oral] "Learning to Substitute Span towards Improving Compositional Generalization"
Pytorch implementation of the paper: "BMN: Boundary-Matching Network for Temporal Action Proposal Generation", along with three new modules to address overfitting issues found in the baseline model, and their ablation studies.
Augmentation for CV using frequency shortcuts
The purpose of this research project is to compare traditional CNNs to vision transformers, can transformers give a higher AUC when classifying Atypical Femoral Fracture / Normal Femoral Fracture?
Unleashing the Power of CNNs for Precise American Sign Language Recognition.
Node Duplication Improves Cold-start Link Prediction
This is an effort to provide different approaches towards human action recognition from video. A method to perform data augmentation on skeletal data so as to achieve a view independent recognition approach is included.
Applying data augmentation to deep-learning-based (CNN) image classification task.
This is the official source code of the paper 'Features kept generative adversarial network data augmentation strategy for hyperspectral image classification'
1st Place (🏆) for Best Face Recognition System in the Face & Gesture Analysis Challenge at UPF
A study that aims to unfold what emotions did Filipino students manifest during a year of Covid-19 quarantines.
Spotify Classification Problem 2023
Disease - Symptom Dataset Cleaning and Augmenting Process
This project investigates the impact of generative AI on the performance of convolutional neural networks (CNNs) in image classification tasks, specifically in the context of limited data.
Solar Flare Prediction through Time Series Data Augmentation
This repository contains code and resources for building a Convolutional Neural Network (CNN) that can recognize American Sign Language (ASL) images. The model is capable of classifying letters in ASL using high accuracy. The process involves data preprocessing, creating a CNN model, training, evaluation, and utilizing the trained model to recogniz
My demonstration of RNN, LSTM, Dropouts, and Data Augmentation Techniques for Texts using Spam and Ham Dataset.
A Python library offering advanced and innovative data augmentation techniques for diverse domains, from medical imaging to environmental data. It enhances dataset diversity, improving model robustness and performance across applications.