During my tenure, I contributed to various projects focusing on computer vision and AI technologies:- Developed custom object detection and tracking models using YOLOv8 with StrongSort, ByteTracker, etc.- Implemented face detection and recognition systems.- Implemented pose estimation and gesture recognition for a known person.- Participated in the development of Hajj crowd counting solutions.- Engaged in multi-label classification tasks.- Integrated multiple AI models for a complete backend system .- Utilized technologies such as WebSocket, WebRTC, Flask, and server-side scripting for efficient communication and data processing.- Implemented speech recognition systems for both text-to-speech and speech-to-text functionalities.- Developed speaker diarization algorithms.- Worked with LLAMA, LLAMA2, OLLAMA, and Langchain frameworks.- Deployed models on Nvidia Jetson and Raspberry Pi platforms for edge computing applications.

- worked on a Face Recognition based System with automated training and testing- Redis, Hetzner, Proxmox, Machine learning, Deep Leanring, Python, Docker- Video Analysis; Anomaly Detection (Abnormal Human Activity Recognition) on Video Analysis for multiple classes with I3DCNN, also for binary classes. - Streaming server for camera to access one camera in multiple model without any delay. - Worked on multiple models with with single camera and vice versa.- Worked on custom object detection model training and real time deployment.- developed Flask based API for real time camera streaming on Web browser.- multiple projects for client including deployment on Raspberry pi.

- worked on Anomaly Detection for healthcare insurance- Distributed Computing on multiple GPU- Horovod with keras for training on multiple GPU

• Gained different type of skills• Enhanced my coding and research skills• Worked and Research on different AI and android Project• Android Application Development

Conducting Research• Writing Research Contents• Worked on Brain Control Intelligent Prosthetic Bionic Leg For Above Knee Amputee• Data Acquisition of Biomedical Sensor (EMG Sensor) and IMU Sensor• Applied Different Filtering Technique of Noisy Digital Signals.(DSP)• implemented Different Deep Learning Technique with Python.• Experienced on EMG Sensors (Biomedical Sensor) Data and Hardware components like Arduino and Motors (Servo and Stepper)