ashshaksharifdeen,Ashshak Sharifdeen,github

🚀 About Me

👋 Hi there! I'm Ashshak, an enthusiastic undergraduate student at the University of Colombo in the Faculty of Technology. I'm passionate about delving into the exciting realms of Computer Vision 👁️ and Robotics 🤖. I thrive on connecting the dots and uncovering similarities between various concepts, leveraging this approach to fuel problem-solving. I'm constantly seeking ways to enhance my skills and refine my ability to tackle challenges effectively 🔍. Outside of academic pursuits, you'll likely find me expanding my professional network and knowledge on LinkedIn 📥. Thanks for stopping by my profile, and I'm eagerly looking forward to connecting with you!

Ashshak Sharifdeen's Projects

agrarian

It's drone platform gives the farmers to access their rice plant LAI inorder to identfy their plant grows, production rate,Nitrogen content in their plant.

alcuberic_drive

School student progress checking, Attendance monitoring using Ai

ashshaksharifdeen

Config files for my GitHub profile.

avr_mic_playground

This repository contains Basic Avr Microcontroller programming and it's circuit

convolutional-neural-networks_cousera

This Repository contains Assignment Notebooks of Convolutional Neural Networks Course offered by DeepLearning.AI

deep-learning

This Repository contains my Deep-Learning and Machine Learning Practice Note books

deepposex-advancing-human-pose-classification-with-deep-learning

DeepPoseX is an innovative research project dedicated to advancing the field of human pose classification using cutting-edge deep learning techniques. Our mission is to push the boundaries of pose recognition, enabling precise and real-time detection of human poses in various applications, from fitness tracking to computer vision.

opencv

Open Source Computer Vision Library

pointcloud_playground

This Respository contains Some basic Point cloud Proccesing Techniques

pose_recognition_vtbilstm

This repository houses the code for a cutting-edge deep learning project that combines the power of Bidirectional LSTM (Long Short-Term Memory) with a custom Hierarchical Video Vision Transformer layer. The project focuses on enhancing video analysis tasks by leveraging advanced techniques from both sequence modeling and vision transformers.