Name
Abstract | ||
|---|---|---|
Convolutional Neural Networks (CNNs) are popular in Advanced Driver Assistance Systems (ADAS) for camera perception. The versatility of the algorithm makes it applicable in multiple applications like object detection, lane detection and semantic segmentation. For image processing to be viable in driver assistance systems, the throughput requirement ranges in the order of a few tens of TeraMACs per second (TMACs). In addition, high accuracy levels of image detection and recognition cannot be compromised for the need for high throughput. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.micpro.2021.104039 | Microprocessors and Microsystems |
Keywords | DocType | Volume |
Convolutional Neural Networks,Hardware accelerator,High-throughput | Journal | 83 |
ISSN | Citations | PageRank |
0141-9331 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sagar Eetha | 1 | 0 | 0.34 |
| P K Sruthi | 2 | 0 | 0.34 |
| Vibha Pant | 3 | 0 | 0.34 |
| Sai Vikram | 4 | 0 | 0.34 |
| Mihir Mody | 5 | 43 | 10.93 |
| Madhura Purnaprajna | 6 | 0 | 1.69 |