Dr. Yue Cao | Image Processing | Best Researcher Award

Dr. Yue Cao | Image Processing | Best Researcher Award

Doctorate at Harbin Institute of Technology, China

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đź“‹ Summary

Yue Cao is a Ph.D. candidate at Harbin Institute of Technology, specializing in computational imaging. His work focuses on noise modeling and image enhancement in extreme low-light conditions, making significant strides in sensor technology and image processing.

Education

  • Ph.D., Computer Application Technology (Sep. 2020 – Present), Harbin Institute of Technology
  • M.S., Computer Software and Theory (Sep. 2017 – Aug. 2020), Shaanxi Normal University
  • B.S., Software Engineering (Sep. 2010 – Aug. 2014), Inner Mongolia University

💼 Internship Experience

  • Industry-Academia-Research Project Intern
    OPPO Research Institute, Shenzhen
    Feb. 2023 – Feb. 2024 (estimated)
    Engaged in noise modeling and parameter calibration of mobile phone sensors, as well as joint denoising, demosaicking, and super-resolution tasks in extremely low-light conditions related to smartphone sensor technology.

🏆 Selected Awards

  • 2020: Winner Award, NTIRE Real Image Denoising Challenge – rawRGB Track
  • 2020: 3rd Place Award, NTIRE Real Image Denoising Challenge – sRGB Track
  • 2014: Outstanding Graduate of Inner Mongolia Autonomous Region, P.R. China
  • 2012: Excellent Three Merit Student Award of Inner Mongolia Autonomous Region, P.R. China

🔬 Research Interests

Dr. Yue’s research interests include noise modeling, image denoising, demosaicking, super-resolution, and sensor technology, with a particular focus on improving imaging performance in challenging environments.

Publications

Physics-guided iso-dependent sensor noise modeling for extreme low-light photography

  • Authors: Yue Cao, Ming Liu, Shuai Liu, Xiaotao Wang, Lei Lei, Wangmeng Zuo
  • Year: 2023

Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessment

  • Authors: Yue Cao, Zhaolin Wan, Dongwei Ren, Zifei Yan, Wangmeng Zuo
  • Year: 2022

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser

  • Authors: Yue Cao, Xiaohe Wu, Shuran Qi, Xiao Liu, Zhongqin Wu, Wangmeng Zuo
  • Year: 2021

Unpaired learning of deep image denoising

  • Authors: Xiaohe Wu, Ming Liu, Yue Cao, Dongwei Ren, Wangmeng Zuo
  • Year: 2020

Ntire 2020 challenge on real image denoising: Dataset, methods and results

  • Authors: Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte, Michael S Brown
  • Year: 2020

Dr. Tirumala Vasu | Image Processing | Excellence In Research

Dr. Tirumala Vasu | Image Processing | Excellence In Research

Doctorate at Presidency University, India

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Academic Background:

Dr. G. Tirumala Vasu is an accomplished Assistant Professor in the E.C.E Department at Presidency University, Bangalore, Karnataka, with over 14 years of extensive experience in academia. He is known for his dedication to teaching, research, and development in the field of Electronics and Communication Engineering. Dr. Vasu has made significant contributions to the academic community, publishing numerous research papers, presenting at national and international conferences, and securing patents. He has a strong background in Digital Image Processing, Deep Learning, and Digital Signal Processing, among other areas. He has also been recognized for his outstanding teaching and research efforts with various awards and honors.

Education:

Dr. Vasu earned his Ph.D. from the National Institute of Technology (NIT), Tiruchirappalli in February 2024, with a thesis titled “Multi Focus, Multi Exposure and Multi Sensor Image Fusion Using Edge Preserving Filters”. He holds an M.Tech in Digital Electronics and Communication Systems from JNTU Anantapur, completed in 2009 with first-class distinction, and a B.Tech in Electronics and Communication Engineering from Sri Venkateswara University, Tirupati, completed in 2007. Additionally, he has distinguished himself academically since his early education, consistently achieving first-class distinction throughout his studies.

Professional Experience:

Dr. Vasu has been serving as an Assistant Professor at Presidency University, Bangalore since July 2018. Previously, he held the same position at Siddharth Institute of Engineering and Technology, Puttur, Andhra Pradesh from June 2012 to May 2018, and at Regency Institute of Technology, Yanam, UT of Puducherry from December 2010 to June 2012. He began his academic career at KSRM College of Engineering, Kadapa, Andhra Pradesh, where he worked from August 2009 to December 2010. Throughout his career, Dr. Vasu has taught a wide range of subjects including Computational Intelligence, Machine Learning, Digital Signal Processing, and more. He has also been actively involved in various academic and research coordination roles.

Research Interests:

Dr. Vasu’s research interests are diverse and include Digital Image and Video Processing, Deep Learning and Machine Learning, Digital Signal Processing, 5G OTFS, Electromagnetic Waves and Transmission Lines, and Antennas and Wave Propagation. He has published 28 papers in international journals, presented at numerous conferences, and published 11 patents. His work has earned him accolades such as Best Paper awards and recognition for his innovative contributions to the field of Electronics and Communication Engineering.

 Publications:

Medical image registration with object deviation estimation through motion vectors using octave and level sampling
  • Authors: Nagarathna, P., Jeelani, A., Fiza, S., Vasu, G.T., Seelam, K.
  • Journal: Automatica
  • Year: 2024
Multi-exposure image fusion using structural weights and visual saliency map
  • Authors: Tirumala Vasu, G., Palanisamy, P.
  • Journal: Multimedia Tools and Applications
  • Year: 2024
Visible and Infrared Image Fusion Using Distributed Anisotropic Guided Filter
  • Authors: Vasu, G.T., Palanisamy, P.
  • Journal: Sensing and Imaging
  • Year: 2023
Improved chimp optimization algorithm (ICOA) feature selection and deep neural network framework for internet of things (IOT) based android malware detection
  • Authors: G.T.V., Fiza, S., Kumar, A.K., Kumar, C.N., Kubra, A.
  • Journal: Measurement: Sensors
  • Year: 2023
CT and MRI multi-modal medical image fusion using weight-optimized anisotropic diffusion filtering
  • Authors: Vasu, G.T., Palanisamy, P.
  • Journal: Soft Computing
  • Year: 2023