DR. PRANTI DUTTA

Dr Pranti is a self-motivated individual looking forward to a thought-provoking and responsible career in research and development.

Experience: 5+ years in research with a Doctorate in Computer Science.

Focus Areas: Computer Vision, Image Processing, Video Processing, Machine Learning, Mathematical Algorithms

Worked on projects like automatic height detection from images, baby length detection, and computer vision based height measurement mobile application. Applied YOLO real time object detection model, MTCNN to locate the child's face in a photograph. Applied HSV color segmentation and Harris Corner detection to locate reference object for calculation of vanishing points and head point. Applied Single View Metrology based 3D reconstruction technique to calculate the height of the child. Achieved an error of (±) 2.14% when compared to true height. Also worked on projects like image inpainting, OCR based on seven segment digits, Solar panel detection, Image labeling, Vehicle counting & classification using YOLOv8 etc.

• Artificial Intelligence for Climate Change Mitigation and Adaptation: Use cases of AI for transport and water management in India. Center for Study of Science, Technology and Policy
• Sep 29, 2022
• Extraction of Features from Video Files Using Different Image Algebraic Point Operations. 2nd International Conference on Image and Graphics Processing (ICIGP 2019), ACM, Singapore, Feb 23, 24 & 25, 2019
• Facial Pain Expression Recognition in Real-Time Videos. Journal of Healthcare Engineering, Article ID 7961427, Hindawi, August 5, 2018
• Detection of Faces from Video Files with Different File Formats. International Conference on Microelectronics, Computing and Communications (MicroCom), NIT Durgapur, IEEE, Jan 24, 2016
• A Contemplation of Facial Expression Recognition System in Real World Applications. International Journal of Advances in Electronics and Computer Science (IJAECS) Volume- 2, Issue-9, Jul 26, 2015
• Demarcating Happy Affect Identification in Faces Using a Mathematical Model. International Journal of Modern Computer Science (IJMCS), Oct 5, 2014
• An Unpretentious Technique for Happy Affect Identification in Faces Using Principal Component Analysis. National Conference on Emerging Trends and Challenges in Information Technology, Sep 30, 2014
• Cataloging of Happy facial Affect using a Radial Basis Function Neural Network. 4th International Conference on Signal and Image Processing (ICSIP 2012), Springer, Dec 14, 2012
• Emancipating of Eigen Faces with the Anecdotal Mathematical Rudiment. International Conference on Mathematics in Engineering and Business Management, Mar 9, 2012