husnejahan Goto Github PK

followers: 19.0 following: 7.0 repos: 380.0 gists: 2.0

Name: Jahan

Type: User

Company: Ryerson university

Bio: Machine Learning Developer

Location: Canada

Hi there 👋

🔭 I’m currently working on
- Building video analytics platform
- Reseach on Computer vision, Medical imaging, Video analytics
🌱 My expertise is in

       -   Adversarial machine learning
       -   Adversarial Training
       -   Model Optimization
       -   Autonomous UAV
       -   ML System Design for video analytics
       -   ML System Design for Medical imaging

📫 How to reach me: [email protected]

Jahan's Projects

2018aicity_teamuw

The winning method in Track 1 and Track 3 at the 2nd AI City Challenge Workshop in CVPR 2018 - Official Implementation

3d-annotation-tool

A graphical user interface to annotate point clouds and 3D data.

3d-deep-learning-with-python

3D Deep Learning with Python, Published by Packt

3d-ru-net

A SlidingWindow-Free Accurate and Fast 3D Medical Image Segmentation Framework

3d_cnn_tensorflow

KITTI data processing and 3D CNN for Vehicle Detection

3pu

Patch-base progressive 3D Point Set Upsampling

59-angular-chatbot-dialogflow

Build a Chatbot with Angular https://angularfirebase.com/lessons/chatbot-in-angular-with-dialogflow-api-ai/

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

adaptive-quantization-modules

Code for "Online Learned Continual Compression with Adaptive Quantization Modules"

aerial-imagery-segmentation

Codebase for the MSc thesis paper Aerial Imagery Pixel-level Segmentation

alert-generation-on-detection-of-suspicious-activity-using-transfer-learning

ADAG (Activity Detector and Alert Generator) aims to take real-time videos from CCTV as an input and pass it to the CNN model created with the help of transfer learning and detect ‘Shoplifting’, ‘Robbery’ or ’Break-In’ in the store and notify it to the owners as soon as it occurs. Finally the main motive is to provide a system that detects suspicious activities without human intervention and generates alert, thus making a huge revolution in today’s surveillance system.

alocc_keras

Keras implementation of Adversarially Learned One-Class Classifier or ALOCC for short.

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

amazon-sagemaker-keras-text-classification

A step-by-step guide that shows how to do text classification by run training/inference for a custom model in Amazon SageMaker

android_client-flask_server

Android app with flask back-end

androidobd

androidvideoplayer

A video player based on Exoplayer

androidwithkotlin

:rocket: These are android sample projects which are written in Kotlin. It covers video streaming, mp3 player, sqlite, location services, custom camera, o-notifications, simple compass etc.

anomalies_by_count

A collaborative Computer Science Project to detect crowd anomalies(i.e. robberies, medical emergencies, gang fights, natural disasters etc.) present in CCTV videos by using the shifting count of people to inform detection