Eliel Keelson

Kwame Nkrumah University of Science and Technology

Papers

Total Citations

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About

Eliel Keelson is a researcher at the forefront of affective computing, with a focused expertise in deep learning algorithms for facial emotion detection and recognition (FER). His work addresses a critical challenge in human-computer interaction: enabling machines to accurately interpret human emotional states from facial expressions. Keelson’s most-cited paper, a comprehensive survey on deep learning algorithms in FER, has garnered 9 citations and serves as a foundational resource for researchers in the field. This work systematically reviews state-of-the-art techniques, highlighting how convolutional neural networks and other deep architectures are revolutionizing the ability to bridge the communication gap between humans and computers. By synthesizing advances in this rapidly evolving domain, Keelson provides a roadmap for developing more intuitive, emotionally aware AI systems. His contributions are particularly significant for applications in mental health monitoring, user experience design, and assistive technologies. As a rising voice in affective computing, Keelson’s research continues to shape how machines perceive and respond to human emotion, promising more natural and empathetic interactions in the digital age.