Name
Abstract | ||
|---|---|---|
Low-cost in-baggage object identification is highly demanded in enhancing public safety and smart manufacturing. Existing approaches usually require specialized equipment and heavy deployment overhead, making them hard to scale for wide deployment. The recent WiFi-based approach is unsuitable for practical deployment as it did not address dynamic environmental impacts. In this work, we propose an ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MASS52906.2021.00018 | 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS) |
Keywords | DocType | ISSN |
Training,Adaptation models,Shape,Safety,Object recognition,Convolutional neural networks,Noise measurement | Conference | 2155-6806 |
ISBN | Citations | PageRank |
978-1-6654-4935-9 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cong Shi | 1 | 489 | 40.60 |
| Tianming Zhao | 2 | 10 | 7.28 |
| Yucheng Xie | 3 | 2 | 2.73 |
| Tianfang Zhang | 4 | 1 | 2.12 |
| Yan Wang | 5 | 2 | 3.07 |
| Xiaonan Guo | 6 | 8 | 5.27 |
| Yingying Chen | 7 | 2495 | 193.14 |