M. Fatih Demirci

About

M. Fatih Demirci is a leading figure in the integration of embedded systems and robotics, with a primary focus on real-time computer vision and hardware acceleration. His research bridges the gap between high-level artificial intelligence and low-level hardware implementation, particularly using Field Programmable Gate Arrays (FPGAs). A major contribution is his pioneering work on a pipelined FPGA architecture for Harris corner detection, designed for mobile robots. This 2013 paper, which has garnered 27 citations, demonstrated how to leverage the parallelizable structure of FPGAs to achieve efficient, real-time feature extraction in resource-constrained environments. More recently, Demirci has advanced the field of industrial automation. His 2020 work, with 23 citations, presents a novel deep learning pipeline for object classification and position estimation using RGB-D sensors, specifically designed for robotized pick-and-place operations. This unified framework showcases his ability to combine sophisticated neural networks with practical robotic control, enabling more autonomous and accurate manipulation tasks. Through these contributions, Demirci has established himself as a key innovator in creating efficient, hardware-aware solutions for next-generation robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Pipelining Harris corner detection with a tiny FPGA for a mobile robot

   27 citations · 2013
2. 2
   Deep Learning-Based Object Classification and Position Estimation Pipeline for Potential Use in Robotized Pick-and-Place Operations

   23 citations · 2020

Key Collaborators

Contact & Links