Jay Kadam Email & Phone Number

Valsad, Gj, In

Atlanta, Georgia, United States

➜ Object Detection with YOLOv4: I implemented the YOLOv4 algorithm for real-time object detection, enabling our visual testing system to identify multiple elements within the application under test accurately. The model's speed and accuracy were optimized, making it ideal for handling complex UI elements in diverse applications.➜ Feature Matching with SIFT and SURF: To handle scenarios where exact object detection was challenging, I incorporated Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) algorithms. These techniques allowed our system to perform feature matching and locate elements based on distinctive visual features, ensuring robustness even with minor variations in UI elements.➜ Transfer Learning with Pre-trained Models: To expedite model training and achieve superior performance, I utilized transfer learning by fine-tuning pre-trained deep learning models like ResNet and MobileNet. This approach helped us overcome data scarcity challenges and achieve impressive results even with limited labeled data.➜ Constant Research and Innovation: Throughout the development process, I actively stayed abreast of the latest AI and computer vision research, attending conferences and engaging in continuous learning. This commitment to innovation enabled us to stay ahead in the ever-evolving field of Automation testing and deliver cutting-edge solutions to our clients.

Master Of Business Administration - Mba, Data Science, A

Bachelor Of Engineering, Computer Science