S. Ariffa Begum

Kalasalingam Academy of Research and Education

Papers

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About

S. Ariffa Begum is a researcher at the forefront of computer vision and deep learning, with a specialized focus on object localization and detection. Her most-cited work, "Object Localization Using Deep Neural Network with Pytorch" (2024), tackles a fundamental challenge in visual recognition: precisely identifying and locating objects within images. This study critically examines bounding box regression techniques, comparing region-based and anchor-based approaches, and provides a practical evaluation using the PyTorch framework. By addressing the critical role of object localization in fields ranging from robotics to medical image analysis, Begum’s research offers valuable insights for developing more accurate and efficient detection systems. Her work contributes to the growing body of knowledge that enables machines to interpret visual data with human-like precision, directly impacting autonomous systems and diagnostic tools. With her focus on accessible, framework-based implementations, Begum is helping to bridge the gap between theoretical advances and real-world deployment, making her a rising voice in the applied deep learning community.