Research

Amran’s paper received Best Paper Award at ICEBEHI 2021

Research / /

Congratulations to Amran! His paper “Investigation of the Unsupervised Machine Learning Techniques for Human Activity Discovery” received the Gold Award in General Electronic Category at the second International Conference on Electronics, Biomedical Engineering and Health Informatics (ICEBEHI) 2021. Amran presented the paper virtually held on 3-4 November 2021. Abstract. Human activity recognition has been considered […]

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Bacha’s paper on hybrid margin-based ROI face detection has been published in Visual Computing

Research / /

Bacha‘s paper on “Face detection and tracking using hybrid margin-based ROI techniques” has been published in Springer’s journal Visual Computing. Congratulations to Bacha! This study is to solve the problem of low accuracy and slow processing speed for real-time face detection and tracking systems. A margin-based region of interest approach with fixed and dynamic margin

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Mateen’s paper presented in BDIOT 2018 at Beijing

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Mateen‘s paper on “Implementation and Evaluation of IoT System Using Cloud Storage Platform” has been accepted in the 2nd International Conference on Big Data and Internet of Things (BDIOT 2018). Abstract. As the internet has become more accessible, the use of Internet of Things (IoT) systems is increasing. An IoT system can be accessed either

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Bacha’s paper presented in ICISPC 2018 at Kuala Lumpur

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Bacha‘s paper on “Using Margin-based Region of Interest Technique with Multi-Task Convolutional Neural Network and Template Matching for Robust Face Detection and Tracking System ” has been accepted in the 2nd International Conference on Imaging, Signal Processing and Communication (ICISPC 2018). The paper was presented at the conference in KL. The presentation received the Best

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Bacha presented his poster in MIWAI 2017

Research / /

Bacha‘s paper on “Hybrid Model with Margin-Based Real-Time Face Detection and Tracking” has been accepted in the 11th Multi-disciplinary International Workshop on Artificial Intelligence (MIWAI 2017). Abstract. Face detection and tracking algorithms mainly suffer from low accuracy, slow processing speed, and poor robustness when meet with real-time setup. The problem becomes crucial in real-time situations

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