Name
Title | ||
|---|---|---|
End-to-End FPGA-based Object Detection Using Pipelined CNN and Non-Maximum Suppression |
Abstract | ||
|---|---|---|
Object detection is an important computer vision task, with many applications in autonomous driving, smart surveillance, robotics, and other domains. Single-shot detectors (SSD) coupled with a convolutional neural network (CNN) for feature extraction can efficiently detect, classify and localize various objects in an input image with very high accuracy. In such systems, the convolution layers extr... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/FPL53798.2021.00021 | 2021 31st International Conference on Field-Programmable Logic and Applications (FPL) |
Keywords | DocType | ISSN |
Convolution,Surveillance,Object detection,Throughput,Feature extraction,Prediction algorithms,Hardware | Conference | 1946-1488 |
ISBN | Citations | PageRank |
978-1-6654-3759-2 | 0 | 0.34 |
References | Authors | |
0 | 10 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anupreetham Anupreetham | 1 | 0 | 0.34 |
| Mohamed O. Ibrahim | 2 | 3 | 6.82 |
| Mathew Hall | 3 | 10 | 1.97 |
| Andrew Boutros | 4 | 25 | 4.61 |
| Ajay Kuzhively | 5 | 0 | 0.34 |
| Abinash Mohanty | 6 | 148 | 8.42 |
| Eriko Nurvitadhi | 7 | 399 | 33.08 |
| Vaughn Betz | 8 | 22 | 7.86 |
| Yu Cao | 9 | 2765 | 245.91 |
| Jae-sun Seo | 10 | 536 | 56.32 |