Lilik Anifah

Papers

Total Citations

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About

Lilik Anifah is a researcher whose work sits at the intersection of robotics, computer vision, and intelligent systems. Her most recognized contribution to date focuses on the development of object detection systems for humanoid soccer robots, utilizing the Darknet YOLO (You Only Look Once) deep learning framework — a cutting-edge approach to real-time visual recognition. In this work, she addresses one of the fundamental challenges in autonomous robotics: enabling robots to accurately identify critical objects on the field, specifically the ball and goal, which are essential for competitive soccer performance. This research, published in 2023 and already accumulating citations, reflects a growing scholarly interest in applying advanced neural network architectures to practical robotics applications. Anifah's contributions are particularly relevant to the field of robot soccer, a domain that serves as a testbed for broader artificial intelligence and autonomous systems research. Her work demonstrates a commitment to bridging theoretical machine learning methods with real-world engineering challenges, making her research valuable to students and practitioners working in robotics, image processing, and intelligent automation systems.