Designing and deploying scalable deep learning pipelines for real-time object detection and segmentation tasks.Integrating state-of-the-art models like YOLO and SAM2 into production systems, enabling seamless input processing and accurate predictions.Automating data annotation, model training workflows, and prediction pipelines for efficient scalability.Implemented an advanced real-time detection system achieving 95% accuracy in Pepsi SKU identification using YOLOv9, trained on… Show more Designing and deploying scalable deep learning pipelines for real-time object detection and segmentation tasks.Integrating state-of-the-art models like YOLO and SAM2 into production systems, enabling seamless input processing and accurate predictions.Automating data annotation, model training workflows, and prediction pipelines for efficient scalability.Implemented an advanced real-time detection system achieving 95% accuracy in Pepsi SKU identification using YOLOv9, trained on 2,000+ annotated images.Deployed production-grade object detection models with Flask API integration, ensuring real-time prediction delivery and operational efficiency.Automated dataset handling and annotation processes, significantly reducing manual effort and enhancing pipeline reliability.Contributed to scaling production workflows, resulting in faster model inference and improved detection accuracy across diverse datasets. Show less

1. Body Measurement System Development: - Generated accurate body measurements from 2D images using advanced computer vision models like Faster R-CNN, YOLACT++, OpenPose, and HMR. - Developed algorithms ensuring precision for both tight-fit and loose-fit clothing.2. Algorithm Design and Accuracy: - Created robust algorithms tailored for high-accuracy body measurements across diverse apparel types.3. Advanced Model Utilization: Leveraged state-of-the-art models… Show more 1. Body Measurement System Development: - Generated accurate body measurements from 2D images using advanced computer vision models like Faster R-CNN, YOLACT++, OpenPose, and HMR. - Developed algorithms ensuring precision for both tight-fit and loose-fit clothing.2. Algorithm Design and Accuracy: - Created robust algorithms tailored for high-accuracy body measurements across diverse apparel types.3. Advanced Model Utilization: Leveraged state-of-the-art models such as Faster R-CNN and OpenPose to create a scalable and reliable body measurement pipeline.4. Precision: Achieved accurate and consistent measurement results, meeting the requirements for diverse clothing styles. 5. Model Implementation: Successfully integrated at least four computer vision models for extracting precise measurements.6. Output Accuracy: Delivered high-quality results in various fitting conditions (tight-fit and loose-fit). Show less

# Resolve students' doubts and answer their questions related to coding and programming# Help students understand the approach and concepts needed to complete their projects# Evaluate students' projects and provide feedback and guidance to improve their coding skills, Resolve students' doubts and answer their questions related to coding and programming , Help students understand the approach and concepts needed to complete their projects , Evaluate students' projects and provide… Show more # Resolve students' doubts and answer their questions related to coding and programming# Help students understand the approach and concepts needed to complete their projects# Evaluate students' projects and provide feedback and guidance to improve their coding skills, Resolve students' doubts and answer their questions related to coding and programming , Help students understand the approach and concepts needed to complete their projects , Evaluate students' projects and provide feedback and guidance to improve their coding skills. Show less