IEEE

Enhancing Few-Shot Image Classification With a Multi-Faceted Self-Supervised and Contrastive Learning Approach

Abstract: One effective approach for solving few-shot classification is learning deep representations that measure the similarity between query images and a few support images of specific categories.
IEEE

AlexCapsNet: An Integrated Architecture for Image Classification With Background Noise

Abstract: Capsule networks (CapsNet) are a pioneering architecture that can encode image features into vectors rather than scalars, addressing the limitations of traditional Convolutional Neural ...
GitHub

Claude Code Skills & Agents Factory

claude-code-skills-factory/ ├── README.md # This file ├── CLAUDE.md # Repository guidance ├── AGENTS.md # Codex CLI documentation (auto-generated) ├── CHANGELOG.md # Version history ├── .claude/ │ ├── ...
GitHub

Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks

The project titled "Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks" aims to develop a robust and accurate machine learning model for the automatic ...