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Ahmad Fakhri Ab. Nasir

Researcher at Universiti Malaysia Pahang

Publications -  37
Citations -  490

Ahmad Fakhri Ab. Nasir is an academic researcher from Universiti Malaysia Pahang. The author has contributed to research in topics: Computer science & Support vector machine. The author has an hindex of 5, co-authored 32 publications receiving 164 citations. Previous affiliations of Ahmad Fakhri Ab. Nasir include Universiti Sultan Zainal Abidin.

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Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

TL;DR: This article provides a comprehensive review of the state-of-the-art of a complete BCI system and a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics.
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A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework.

TL;DR: The results obtained herein demonstrated that the Faster R-CNN model offers a high-performing rice leaf infection identification system that could diagnose the most common rice diseases more precisely in real-time.
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A machine learning approach of predicting high potential archers by means of physical fitness indicators.

TL;DR: These findings could be valuable to coaches and sports managers to recognise high potential archers from a combination of the selected few physical fitness performance indicators identified which would subsequently save cost, time and energy for a talent identification programme.

A Study of Image Processing in Agriculture Application under High Performance Computing Environment

TL;DR: The steps of image analysis done in some image processing focusing on agriculture application and also the details analysis of parallel and distributed image processing are reviewed.
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Technical and tactical performance indicators discriminating winning and losing team in elite Asian beach soccer tournament.

TL;DR: The Mann-Whitney U test analysis indicated that the WT is statistically significant from the LT based on the performance indicators determined from the standard mode model of the DA, which could serve useful to the coaches as well as performance analysts as a measure of profiling successful performance and enables team improvement with respect to the associated performance indicators.