mojtaba-nafez

Deep-learning-Course

IUST_Consultant

Software Engineering Course

Operating_System_2021

ai-iust-992

AnomalyCLIP

Official implementation for AnomalyCLIP (ICLR 2024)

badnets-pytorch

Simple PyTorch implementations of Badnets on MNIST and CIFAR10.

blogpy

Blogpy project based on Python 3.8 and Django 2.2

Blogpy-1

Blogpy project based on Python 3.8 and Django 2.2

burgur_builder_reactjs

a deep selfstudy on react js

CodART

Source Code Automated Refactoring Toolkit

Consultant

CSI

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

CSI-corruption-evaluation

Deep-Active-Learning-via-Open-Set-Recognition

Active Learning using Openset Recognition

eoe

Repository for the Exposing Outlier Exposure paper

HTTPS

invariant-anomaly-detection

Implementation of robust deep anomaly detection models using Partial Conditional Invariant Regularization (PCIR). Accepted to NeurIPS 2023.

laboratory_microcontroller

ML-Course-AIMedic

mojtaba-nafez

mojtaba-nafez.github.io

Photo_Wall_reactjs

Practice reactjs

Pytorch-UNet

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

recipe-app-api_django-self-study

ReContrast

RoCL

Code for the paper "Adversarial Self-supervised Contrastive Learning" (NeurIPS 2020)

UniAD

[NeurIPS 2022 Spotlight] A Unified Model for Multi-class Anomaly Detection

vaal

Variational Adversarial Active Learning (ICCV 2019)

YOLO

You only look once (YOLO)

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite