Deisy Chaves

Papers

Total Citations

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About

Deisy Chaves is a researcher whose work lies at the intersection of computer vision and applied artificial intelligence, with a particular focus on the automatic localization of objects within images. Her most cited paper, "Una Revisión Sistemática de Métodos para Localizar Automáticamente Objetos en Imágenes" (2018, 12 citations), provides a comprehensive systematic review of techniques for precise object detection, a foundational challenge for applications ranging from industrial visual inspection to computer-assisted clinical diagnosis and obstacle detection. This work synthesizes and evaluates key methodologies, offering a valuable resource for researchers and practitioners seeking to advance automated image analysis. Chaves’ contributions are especially relevant to fields where accuracy and efficiency in object localization are critical, such as in medical imaging and autonomous systems. While her citation count reflects a growing recognition of her systematic approach to surveying complex technical landscapes, her research underscores the practical importance of bridging algorithmic development with real-world deployment. For students and researchers exploring computer vision, Chaves’ work serves as a clear entry point into understanding the state of the art in object localization and its transformative potential across industries.