Mr. Suranjan Goswami | Computer Vision | Best Researcher Award
PhD Research Scholar | Indian Institute of Information Technology, Allahabad | India
Short Biography 🌟
Suranjan Goswami is a dedicated AI and Computer Vision Engineer known for his expertise in developing and deploying advanced AI and Machine Learning models. With a strong focus on Python programming, feature engineering, and data analysis, he enhances project performance and efficiency in various technological domains.
Profile
Education 📚
Suranjan is currently pursuing a Ph.D. in Computer Vision from the Indian Institute of Information Technology (IIITA) in Prayagraj, expected to be completed by December 2024. He holds a Master’s degree in Computer Science Engineering from the Institute of Engineering And Management in Kolkata, where he graduated with an impressive CGPA of 8.25.
Experience 💼
Suranjan’s professional journey includes roles such as Senior Research Engineer at Ola Electric, where he leads the Vision Pipeline for integrated automation of mechanical tasks. Previously, he served as a Computer Vision Engineer at Trimble, contributing to the development and deployment of advanced AI models aimed at enhancing performance across various applications.
Research Interests 🔬
His research interests span across Computer Vision, Thermal Image Processing, Colorization, Deep Learning, and Image enhancement. He is particularly focused on the mathematical foundations of Deep Learning and applications like 3D Point Clouds and Path Planning.
Award 🏆
Suranjan is a multiple-time qualifier of the Gate exam and was recognized as the East India Finalist at FameLab 2016-17 by the British Council India. His contributions to research and academia have earned him an Expert Author Certificate from EzineArticles.com.
Publications 📄
[2024] An Image Information Fusion based Simple Diffusion Network leveraging the Segment Anything Model for Guided Attention on Thermal Images producing Colorized Pedestrian Masks, Information Fusion. doi: 10.1016/j.inffus.2024.102618 (Cited by 2 articles)
[2022] A Novel Deep Learning Method for Thermal to Annotated Thermal-Optical Fused Images, CVIP 2022, CCIS 1776. (Cited by 5 articles)
[2021] Thermal Visual Paired Dataset. doi: 10.21227/jjba-6220 (Cited by 10 articles)
[2021] Thermal Optical Annotated Multi Class Image Dataset. doi: 10.21227/80yz-h738 (Cited by 7 articles)
[2021] OptiEnc: On the Path to the Optimal Encoder-Decoder for Thermal Image Colorization for Cross Domain Colorized Images, arXiv:2101.06910
[2020] A simple deep learning based image illumination correction method for paintings, Pattern Recognition Letters 138: 392-396. (Cited by 15 articles)