Papers
3
Total Citations
10
H-Index
2
About
Nanik Suciati is a researcher whose work sits at the intersection of computer vision, robotics, and artificial intelligence, with a particular focus on enabling machines to perceive and interact with their environments. Her key research areas include face recognition, autonomous robotics, and generative models for image synthesis. In one of her notable contributions, she explored parallel computing to accelerate the WaveCluster algorithm for face recognition, addressing the critical need for faster system responses in applications like video surveillance and robot navigation. She has also advanced autonomous robotics, developing image segmentation techniques using multilayer neural networks and HSV color features to guide wheeled soccer robots in fully autonomous, real-time matches. More recently, Suciati has ventured into creative AI, employing Generative Adversarial Networks and deep reinforcement learning to generate sketches from real object images—a step toward machines that can produce art. While her most cited papers have garnered modest citation counts (up to 4 citations), her work demonstrates a sustained engagement with practical, applied problems in robotics and vision, contributing to the development of more intelligent and responsive autonomous systems.
Research Focus
Key Achievements
Top Papers
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