Projects in Awesome Lists by Aleedm
A curated list of projects in awesome lists by Aleedm .
https://github.com/aleedm/glomerulearn-advanced-deep-learning-for-kidney-tissue-analysis
A project leveraging machine learning for the identification and classification of glomeruli in renal biopsy images. Utilizes SegNet and U-Net for segmentation and explores unsupervised clustering for sclerosed glomeruli classification
autoencoder cnn-model semantic-segmentation supervised-learning unsupervised-classification
Last synced: 19 Jun 2025
https://github.com/aleedm/neat-quixo
This repository showcases a project where the NEAT algorithm, which dynamically evolves neural networks by adjusting both their architecture and weights, is applied to develop an advanced game-playing agent. The project demonstrates NEAT's capability to create optimized strategies for complex gameplay scenarios.
neuroevolution-of-augmenting-topologies quixo reinforcement-learning
Last synced: 22 May 2026
https://github.com/aleedm/real-time-domain-adaptation-in-semantic-segmentation
This repository contains research on real-time domain adaptation in semantic segmentation, aiming at bridging the gap between synthetic and real-world imagery for urban scenes and autonomous driving, utilizing STDC models and advanced domain adaptation methods.
depthwise-separable-convolutions domain-adaptation generative-adversarial-network real-time-semantic-segmentation
Last synced: 18 Mar 2025
https://github.com/aleedm/multi-platform-screen-grabbing-utility
This Rust-based utility captures and processes screens with ease across Windows, macOS, and Linux. Featuring a user-friendly interface, it supports area selection, customizable hotkeys, multiple formats, and clipboard copying. Optional delay timer, save preferences, and multi-monitor handling enhance its versatility.
Last synced: 18 May 2026
https://github.com/aleedm/alphazero-quixo
This repository develops an AlphaZero-inspired agent for Quixo, leveraging deep learning and Monte Carlo Tree Search (MCTS) for strategy enhancement. It emphasizes self-play, dynamic data management, and exploration-exploitation balance in MCTS, aiming for peak performance in Quixo.
alphazero-inspired monte-carlo-tree-search quixo reinforcement-learning
Last synced: 20 May 2026
https://github.com/aleedm/sick-summarization
This repository explores enhancing dialogue summarization with commonsense knowledge through the SICK framework, evaluating models on dialogue datasets to assess commonsense's impact on summarization quality.
bart-model comet commonsense-knowledge dialogue-summarization natural-language-processing pegasus-model sbert t5-model
Last synced: 18 Mar 2025