Polina Akselrod

Papers

Total Citations

122

H-Index

About

Polina Akselrod is a leading researcher in embedded vision systems, with a focus on high-speed, low-cost implementations of synthetic vision for applications ranging from micro-robots and unmanned aerial vehicles to imaging sensor networks and wireless devices. Her most-cited work, "Large-Scale FPGA-Based Convolutional Networks" (2011, 122 citations), represents a landmark contribution to the field, demonstrating how field-programmable gate arrays can enable real-time object recognition and categorization in resource-constrained environments. This paper has become a foundational reference for engineers seeking to deploy convolutional neural networks in embedded systems without relying on expensive, power-hungry hardware. Akselrod’s research bridges the gap between theoretical advances in deep learning and practical, deployable vision systems, making her work highly influential in both academia and industry. Her achievements underscore a commitment to democratizing intelligent vision technology, enabling autonomous systems to perceive and interact with their surroundings efficiently. For students and researchers exploring edge computing or real-time computer vision, Akselrod’s contributions offer a critical roadmap for balancing computational demands with real-world constraints.