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All Journal Liaison Journal of Engineering
naufal azzam, julian
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT

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Advancement in computer vision: Unveiling the spectrum of possibilities naufal azzam, julian; normalisa
Liaison Journal of Engineering Vol. 3 No. 2 (2023): Vol III
Publisher : Liaison Journal of Engineering

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Abstract

This article provides a comprehensive overview of the rapidly growing field of computer vision, tracing its historical origins, outlining fundamental principles, examining industry applications, addressing ethical challenges, and providing an outlook on future directions. Key topics include image processing techniques, feature extraction, pattern recognition, neural networks, use cases in areas such as healthcare and transportation, bias and privacy considerations, as well as new research in explainable artificial intelligence and multi-modal learning. This analysis outlines how computer vision is transforming human-computer interaction by improving visual perception and understanding while emphasizing the need for responsible and transparent development. Keywords: Computer Vision, Image Processing, Neural Network, Artificial Intelligence, Multi-modal Learning.
Enhancing Sportirena testing through custom Selenium Automation tools for PT Technova naufal azzam, julian; atmadiputra, pradana; normalisa
Liaison Journal of Engineering Vol. 4 No. 1 (2024): Vol 4
Publisher : Liaison Journal of Engineering

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This research paper, entitled "Improving the Testing of Sportirena through Personalized Selenium Automation Tools," highlights the urgent requirement for automated testing within the Sportirena platform. In a similar manner to enhancing fire resistance in composite sandwich panels, which aims to strengthen against potential dangers, our investigation concentrates on enhancing the reliability of Sportirena's application. We have developed customized automation tools, comparable to the addition of fire retardants, utilizing Selenium, with a specific focus on user authentication. The results demonstrate significant improvements in testing efficiency, coverage, and defect detection when compared to manual techniques. The insights obtained from existing literature support our findings and validate the chosen methodology. By drawing parallels between fire resistance in composite panels and automated testing in Sportirena, this study contributes to the overall objective of ensuring safety and resilience in intricate systems. Keywords: testing, efficiency, coverage, and defect detection.
Co-Authors atmadiputra, pradana Normalisa