Muhammad Faizan's Projects
Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).
This is the official repository for the paper "3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers"
This repository contains C++ implementation of A* search algorithm for finding path to goal state for 8 puzzle problem in AI.
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
Icon Matching with Shape Context Descriptors.
Solution of The AI City Challenge 2022 Track 1
The 1st place solution of track2 (Vehicle Re-Identification) in the NVIDIA AI City Challenge at CVPR 2021 Workshop.
This is Andrew NG Coursera Handwritten Notes.
Course assignments
Automated Machine Learning with scikit-learn
:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
:sunglasses: A curated list of awesome MLOps tools
Resources for Multiple Object Tracking (MOT)
[MedIA Journal] An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
A Python implementation of global optimization with gaussian processes.
Multimodal Brain mpMRI segmentation on BraTS 2023 and BraTS 2021 datasets.
Caffe: a fast open framework for deep learning.
On the Unreasonable Effectiveness of Centroids in Image Retrieval
the AI-native open-source embedding database
[TMI2023] Context Label Learning: Improving Background Class Representations in Semantic Segmentation.
Computer Vision course for CS bachelors in UCU (2019)
A technical report on convolution arithmetic in the context of deep learning
Convolution Neural Networks implementation in TensorFlow
This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
Fully automated code for Covid-19 detection from CT scans from paper: https://doi.org/10.1016/j.bspc.2021.102588
YOLO has many variants such as YOLOv5, YOLOv4, YOLOv7, and YOLOv8. Sometimes, it's important to use cropped annotations i.e. to train a second stage classifer etc.