Lambert Schomaker
Papers
14
Total Citations
415
H-Index
10
About
Lambert Schomaker is a versatile researcher whose work spans computer vision, assistive technology, robotics, and machine learning. He is perhaps best known for his pioneering contributions to text detection and recognition from natural scene images, motivated by a deeply human application: helping visually impaired individuals navigate text-rich environments. His 2004 system for camera-based text reading (147 citations) laid important groundwork for what would become a central challenge in computer vision, with follow-up work in 2005 refining detection methods for real-world deployment. Schomaker's research portfolio later expanded significantly into reinforcement learning and robotic motion planning, where he has explored curriculum learning, self-imitation learning, and experience-based planning to address the perennial data-efficiency problem in training autonomous robots. His 2020 work on curriculum-accelerated reinforcement learning (52 citations) reflects this ambition. Notably, his intellectual curiosity extends to cognitive theory, as evidenced by his philosophical engagement with anti-representationalism in cybernetic systems. With contributions ranging from robotic grasp synthesis to indoor localization using deep learning, Schomaker exemplifies the kind of broad, interdisciplinary researcher whose work bridges fundamental science and practical application.
Research Focus
Key Achievements
Top Papers
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- 6Self-Imitation Learning by Planning17 citations · 2021
- 7Learning to Grasp 3D Objects using Deep Residual U-Nets13 citations · 2020
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