Sang-Woo Ban

Kyungpook National University, Dongguk University

Papers

Total Citations

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About

Sang-Woo Ban is a leading researcher in biologically motivated computer vision and autonomous mental development for intelligent robotics. His work focuses on creating computational models that mimic the human visual system, enabling robots to perceive and interact with their environments more naturally. Ban’s most influential contribution is a real-time selective attention model, published in 2005 (11 citations), which allows robots to perform context-free object searches—a crucial step toward autonomous mental development. He extended this framework to novelty detection in dynamic environments (2006, 6 citations), demonstrating robust performance even with affine-transformed or noisy scenes, a key capability for developmental robots. Ban also developed a biologically motivated face-selective attention system (2006, 5 citations) that integrates bottom-up saliency with task-specific cues to reliably identify faces in complex natural scenes. His research bridges neuroscience and robotics, providing foundational algorithms for machines that learn and adapt. With a citation impact that underscores the relevance of his biologically inspired approaches, Ban’s work continues to influence the design of intelligent, perceptually aware robotic systems.