Jayanta Kumar Dutta

Title: Jayanta Kumar Dutta: Innovator in Machine Learning and Object Detection

Introduction

Jayanta Kumar Dutta is a prominent inventor based in Sunnyvale, CA. He has made significant contributions to the fields of machine learning and object detection, holding a total of 5 patents. His innovative work focuses on enhancing the efficiency of video analysis and data acquisition for object recognition.

Latest Patents

Dutta's latest patents include groundbreaking technologies such as "Automated Key Frame Selection" and "Trajectory Design for Image Data Acquisition for Object Detection/Recognition." The first patent addresses the identification of key frames in videos, which are crucial for training machine learning models. This process involves object detection to identify relevant frames, feature extraction to generate raw feature vectors, and compressing these vectors into lower-dimensional clusters. The key frames are then filtered from these clusters to create a representative dataset of the video.

The second patent outlines a vehicle designed for collecting image data of target objects to generate classifiers. This vehicle is equipped with an image sensor and an electronic processor that determines potential trajectories for optimal data collection. The processor evaluates the number of views of the target object captured along each trajectory, ultimately selecting the most effective path for data acquisition.

Career Highlights

Jayanta Kumar Dutta is currently employed at Robert Bosch GmbH, where he continues to develop innovative solutions in his field. His work has significantly advanced the capabilities of machine learning applications in real-world scenarios.

Collaborations

Dutta collaborates with talented individuals such as Naveen Ramakrishnan and Yumi Kondo, contributing to a dynamic and innovative work environment.

Conclusion

Jayanta Kumar Dutta's contributions to machine learning and object detection exemplify the impact of innovation in technology. His patents not only enhance the efficiency of video analysis but also pave the way for advancements in data acquisition methods.