Marco Balsi
Papers
8
Total Citations
54
H-Index
4
About
Marco Balsi is a researcher whose work sits at the intersection of robotics, computer vision, and neuromorphic computing. His primary research focus is on using Cellular Neural Networks (CNNs) for real-time, on-board image processing in autonomous mobile robots. Balsi’s major contributions include developing novel algorithms for tracking and obstacle avoidance that leverage the parallel computation capabilities of CNNs, and implementing these algorithms on FPGA hardware to achieve speeds far exceeding traditional software emulations. His most cited paper, "Robot vision with cellular neural networks: a practical implementation of new algorithms" (2006, 18 citations), demonstrates a complete vision-guided autonomous robot system. Balsi also explored advanced concepts like foveated, space-variant CNN architectures for optical flow computation, and optimized FPGA emulations of CNN-Universal Machines. His work is notable for bridging theoretical neural network models with practical, real-time robotic applications, showing that complex visual tasks can be performed efficiently on compact, low-power hardware.
Research Focus
Key Achievements
Top Papers
- 1
- 2Guiding a mobile robot with cellular neural networks13 citations · 2002
- 3Real time vision by FPGA implemented CNNs7 citations · 2006
- 4Focal-plane optical flow computation by foveated CNNs6 citations · 2002
- 5Optimized cellular neural network universal machine emulation on FPGA3 citations · 2007
- 6Robot Vision Using Cellular Neural Networks3 citations · 2003
- 7Tracking for a CNN guided robot2 citations · 2006
- 8Cellular Neural Networks for Mobile Robot Vision2 citations · 2001