My mentor, Professor Iris Bahar, is a computer science and computer engineering professor at Brown University. Her research interests include computer architecture; computer-aided design for synthesis, verification and low-power applications; design, test, and reliability issues for nanoscale systems; and most recently, design of robotic systems.
Multi-SpooNN: A Lightweight Neural Network for Multiple Object Detection
Real-time object detection is essential for autonomous robots to perform tasks in human en- vironments. As a result, many autonomous robots rely on small, efficient neural networks. SpooNN is a lightweight convolutional neural network (CNN) for object detection that is op- timized for FPGA implementation. However, the network only supports single object de- tection without classification. In this project, we extend the network capability to detect and classify multiple objects and then evaluate network performance on various datasets appropri- ate for autonomous robots.
Click here to read my final report.
Click here to see my poster.