Pinned Repositories
Computational-Genomics-Course-Project
Using different feature selection methods, like genetic algorithm and filter‑based method (using double RBF kernel), to reduce the high dimension of gene expression profile data and then train a classifier based on them.
Computer-Vision-Course-Project
synopsis videos of surveillance cameras through detecting moving objects, tracking them during their presence in the video, constructing temporal‑spatial tubes of them, and finally reconstructing the video to a more abstract form.
Deep-learning-Course-Practical-Assignments
Practical assigments of Deep learning course.
Deep-Reinforcement-Learning-Practical-Assignments
This repository contains the practical assignments for a Deep Reinforcement Learning course. Throughout these assignments, we implemented various advanced methods, including Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), and Soft Actor-Critic (SAC), to solve a range of challenging problems.
Embedding-Matching-with-Self-Supervised-Learning
Embedding Matching with Self Supervised Learning
Neural_encoding
in this project, we use different methods to decrease dimension of neural data, then we used these structures and encoded signals to predict other correlated signals.
Registration-of-Lumbar-Spine-Image
Lumbar Spine (L1-L5) Registration to Atlas Using Point Cloud Extraction and Coherent Point Drift Algorithm.
Sentiment-Detection
Sentiment detection using multimodal (image and text) data
style-augmentation
PyTorch implementation of neural style randomization for data augmentation
voxelmorph
Unsupervised Learning for Image Registration
mohammad-kalbasi's Repositories
mohammad-kalbasi/Computational-Genomics-Course-Project
Using different feature selection methods, like genetic algorithm and filter‑based method (using double RBF kernel), to reduce the high dimension of gene expression profile data and then train a classifier based on them.
mohammad-kalbasi/Computer-Vision-Course-Project
synopsis videos of surveillance cameras through detecting moving objects, tracking them during their presence in the video, constructing temporal‑spatial tubes of them, and finally reconstructing the video to a more abstract form.
mohammad-kalbasi/Deep-learning-Course-Practical-Assignments
Practical assigments of Deep learning course.
mohammad-kalbasi/Deep-Reinforcement-Learning-Practical-Assignments
This repository contains the practical assignments for a Deep Reinforcement Learning course. Throughout these assignments, we implemented various advanced methods, including Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), and Soft Actor-Critic (SAC), to solve a range of challenging problems.
mohammad-kalbasi/Embedding-Matching-with-Self-Supervised-Learning
Embedding Matching with Self Supervised Learning
mohammad-kalbasi/Neural_encoding
in this project, we use different methods to decrease dimension of neural data, then we used these structures and encoded signals to predict other correlated signals.
mohammad-kalbasi/Registration-of-Lumbar-Spine-Image
Lumbar Spine (L1-L5) Registration to Atlas Using Point Cloud Extraction and Coherent Point Drift Algorithm.
mohammad-kalbasi/Sentiment-Detection
Sentiment detection using multimodal (image and text) data
mohammad-kalbasi/style-augmentation
PyTorch implementation of neural style randomization for data augmentation
mohammad-kalbasi/voxelmorph
Unsupervised Learning for Image Registration