Özet
As autonomous systems evolve, they have begun to interact more with their environment. To execute their operational cycles flawlessly, it is critical for these systems to perceive their surroundings at high processing speeds. Additionally, such systems may have constraints related to volume, weight, and energy consumption. Our study focuses on executing high-speed perception cycles that meet these constraints and enable environmental interaction. The real-time operational performance of these cycles was examined on a selected edge device. Among the evaluation metrics, we included the "number of processed images per unit of energy consumed,"which is not commonly found in similar studies. The results clearly indicate that edge devices hold significant potential for real-time point cloud segmentation.
| Tercüme edilen katkı başlığı | Real-Time 3D Point Cloud Segmentation on Edge Devices |
|---|---|
| Orijinal dil | Türkçe |
| Ana bilgisayar yayını başlığı | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings |
| Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Elektronik) | 9798331566555 |
| DOI'lar | |
| Yayın durumu | Yayınlandı - 2025 |
| Etkinlik | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Istanbul, Turkey Süre: 25 Haz 2025 → 28 Haz 2025 |
Yayın serisi
| Adı | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings |
|---|
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| ???event.eventtypes.event.conference??? | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 |
|---|---|
| Ülke/Bölge | Turkey |
| Şehir | Istanbul |
| Periyot | 25/06/25 → 28/06/25 |
Bibliyografik not
Publisher Copyright:© 2025 IEEE.
Keywords
- Edge device
- real time
- segmentation
Parmak izi
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