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Dr Jari Korhonen

Dr Jari Korhonen
Dr Jari Korhonen
Dr Jari Korhonen

Senior Lecturer

Accepting PhDs

About
Email Address
jari.korhonen@abdn.ac.uk
Office Address
328 Meston Building
Old Aberdeen Campus
Meston Walk
AB24 3UE

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School/Department
School of Natural and Computing Sciences
Google Scholar
Pure
ORCiD

Biography

I am an experienced researcher in computer science, specialised in multimedia technologies and Quality of Experience (QoE) in particular. I received my MSc degree in information engineering at University of Oulu, Finland, in 2001, and PhD in telecommunications and signal processing at Tampere University of Technology, Finland, in 2006. In my early career, I worked as a Research Engineer at Nokia Research Center, Tampere, Finland, from 2001 to 2006, before moving to academia. Before joining the University of Aberdeen, I was working at Shenzhen University, China, from 2017 to 2022.

My past research experience covers both telecommunications and signal processing aspects of multimedia communications. My current research focus primarily on visual quality assessment, and I have contributed to several models for predicting perceived image and video quality directly from the signal. As a part of this work, I have been principal investigator (PI) for a project funded by National Natural Science Foundation of China (NSFC) from 2018 to 2021. Most recently, I have studied deep learning techniques applied to visual quality assessment, as well as other related computer vision problems.

In addition to my research work, I have experience of teaching several courses in the fields of visual communications, signal processing, and telecommunications. I have also supervised and co-supervised several student projects at BSc, MSc and PhD levels. 

Qualifications

  • PhD Telecommunications and Signal Processing 
    2006 - Tampere University of Technology, Finland 
  • MSc Information Engineering 
    2001 - University of Oulu, Finland 

External Memberships

  • IEEE Member

Latest Publications

View My Publications

Research

Research Areas

Accepting PhDs

I am currently accepting PhDs in Computing Science.

Please get in touch if you would like to discuss your research ideas further.

Email Me

Computing Science

Accepting PhDs
View Research Area

Research Specialisms

  • Artificial Intelligence
  • Computer Vision
  • Multimedia Computing Science

Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is HESA open data, published under the Creative Commons Attribution 4.0 International licence.

Blind Image and Video Quality Assessment

Jari Korhonen has several years of experience of working on automated prediction of image and video quality, with focus on blind models for user generated photos and videos. Several models based on his work, such as Two-Level Video Quality Model (TLVQM), are publicly available.

Source code in GitHub

Funding and Grants

  • National Natural Science Foundation of China (NSFC) Grant 61772348: "Quality assessment for consumer video applications," 2018-21 (Shenzhen University).
Teaching

Teaching Responsibilities

I am currently course co-ordinator for the following SCNU Joint Institute BSc courses:

I also supervise coursework projects for the following SCNU Joint Institute BSc courses:

In addition, I supervise BSc thesis projects and I am course co-ordinator for the CS programme in JC4000 Graduation Thesis.

Publications

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  • Blind Natural Video Quality Prediction via Statistical Temporal Features and Deep Spatial Features

    Korhonen, J., Su, Y., You, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

  • Motion JPEG Decoding via Iterative Thresholding and Motion-Compensated Deflickering

    Belyaev, E., Bie, L., Korhonen, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

  • Attention Boosted Deep Networks for Video Classification

    You, J., Korhonen, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

  • Blind Natural Image Quality Prediction Using Convolutional Neural Networks and Weighted Spatial Pooling

    Su, Y., Korhonen, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

  • Two-Level Approach for No-Reference Consumer Video Quality Assessment

    Korhonen, J.
    IEEE Transactions on Image Processing, vol. 28, no. 12, pp. 5923-5938
    Contributions to Journals: Articles

  • Assessing Personally Perceived Image Quality via Image Features and Collaborative Filtering

    Korhonen, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

  • Deep Neural Networks for No-Reference Video Quality Assessment

    You, J., Korhonen, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

  • Optimizing the Parameters for Post-processing Consumer Photos via Machine Learning

    Bie, L., Wang, X., Korhonen, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings

  • Study of the Subjective Visibility of Packet Loss Artifacts in Decoded Video Sequences

    Korhonen, J.
    IEEE Transactions on Broadcasting, vol. 64, no. 2, pp. 354-366
    Contributions to Journals: Articles

  • Learning-based Prediction of Packet Loss Artifact Visibility in Networked Video

    Korhonen, J.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
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