Experimenting with CNN architectures for image classification and methods to improve training with small datasets (semi-supervised learning).
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Updated
Jul 27, 2018 - Python
Experimenting with CNN architectures for image classification and methods to improve training with small datasets (semi-supervised learning).
Advanced Scheduling Algorithm for Managing Pseudo Labels in Semi-Supervised Learning
This repository features detailed explanations of each topic along with a project on each topic of Machine learning.
This is one of my micro project that aims to prepare image dataset from a video input and annotates it automatically.
Implementation of semi and self supervised learning on Imbalanced Dataset
Deep Semisupervised Cross-modal Retrieval/Cross-view Recognition (IEEE TCYB 2022, PyTorch Code)
PyTorch implementation of Bayesian Graph Convolutional Networks using Neighborhood Random Walk Sampling to supplement my Honors Thesis.
Exercises from IT3030 V20
Exploring optimization methods like Gradient Descent and BCGD in semi-supervised learning for rice seeds classification
Code implementation of our paper "Exploring Domain-specific Contrastive Learning with Consistency Regularization for Semi-supervised Medical Image Segmentation "
Master's Thesis Project Demo
Dissertação de Mestrado apresentada ao Programa de Pós-Graduação em Informática - PPGI da Universidade Federal do Espírito Santo - UFES
Semisupervised classification methods (SSC) with Spark-ML, study and implementation
Auto Semi-supervised Outlier Detection for Malicious Authentication Events
Implementation of Co-training Regressors (COREG) semi-supervised regression algorithm from Zhou and Li, 2005.
Unofficial Pytorch Implementation of 'FixMatch- Simplifying Semi-Supervised Learning with Consistency and Confidence'
The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.
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