Digital Information Computation And Retrieval (DICR) Research Group | Faculty of Computer Science and Information Technology
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Digital Information Computation and Retrieval (DICR) Research Group

Current advancements in digital technologies have caused an explosion in the volume and diversity of document collections, which include textual, image, audio and video. This has spurred widespread interest in media-specific information retrieval and its related computational research. The DICR research group focuses on investigating techniques in managing large document collections, transforming data into computational representations and devising strategies for storage, processing, organisation, retrieval and interaction with these digital document collections. The main research fields that members are actively involved in include Information Retrieval; Intelligent Multimedia Data Processing, Analysis and Access; Natural Language Processing; Multimodal Sentiment Analysis; Multimodal Interaction and Query Technologies; Image and Video Processing and Sense-making; Speech and Audio Processing; Music and Computing; Web and Search Engine Technologies; Multimedia Analytics and Emerging Trends in Multimedia Big Data. For more information please click here.

 

Group members:

NAME

EXPERTISE

Assoc. Prof. Dr. Shyamala C. Doraisamy (Leader)

shyamala@upm.edu.my

Speech and Audio Processing, Multimedia Analytics, Music Information Retrieval

Assoc. Prof. Dr. Muhamad Taufik Abdullah

mta@upm.edu.my

Information Retrieval, Multimedia Computing

Dr. Azreen Azman

azreenazman@upm.edu.my

Information Retrieval, Text Mining

Dr. Alfian Abd. Halin

alfian@upm.edu.my

Image and Audio Processing using Machine Learning, Pattern Recognition

Dr. Mas Rina Mustaffa

masrina@upm.edu.my

Multimedia Systems and Applications, Content-based Image Retrieval, Pattern Recognition, Image Processing

Nurul Amelina Nasharuddin

nurulamelina@upm.edu.my

Cross-lingual Information Retrieval, Multimedia Computing

 

Current Research Projects/Grants:

  1. Effective Content-based Fish Species Image Retrieval based on Enhanced Zernike-Moments-Local Directional Pattern (FRGS)

Duration: 2016 – 2018

Project leader: Dr. Mas Rina Mustaffa

 

  1. Aesthetics Energy of Image Color-based Point of Regard Estimation for Distance Independent Non-Intrusive Eye Gaze Tracking (FRGS)

Duration: 2014 – 2017

Project leader: Dr. Alfian Abdul Halin

 

  1. An Effective Model to Predict Sentiment Influence within Social Media based on Information Foraging Theory (FRGS)

Duration: 2015 - 2017

Project leader: Dr. Azreen Azman

 

  1. Feature-based Document Alignment Method for High Accuracy in Aligning Malay and English Comparable News Collection (FRGS)

Duration: 2014 – 2017

Project leader: Assoc. Prof. Dr. Muhamad Taufik Abdullah

 

 

Updated:: 24/05/2017 [amir_peli]

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Faculty of Computer Science and Information Technology
Universiti Putra Malaysia
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