Szczegóły publikacji
Opis bibliograficzny
Efficient object detection in fused visual and infrared spectra for edge platforms / Piotr Janyst, Bogusław CYGANEK, Łukasz Przebinda // W: Data Analytics in System Engineering : proceedings of 7th Computational Methods in Systems and Software 2023, Vol. 4. — Cham : Springer, cop. 2024. — (Lecture Notes in Networks and Systems ; ISSN 2367-3370 ; vol. 935). — ISBN: 978-3-031-54819-2; e-ISBN: 978-3-031-54820-8. — eds. Radek Silhavy, Petr Silhavy. — S. 243–253. — Bibliogr., Abstr. — B. Cyganek - dod. afiliacja: MyLED Inc., Kraków
Autorzy (3)
- Janyst Piotr
- AGHCyganek Bogusław
- Przebinda Łukasz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 156181 |
|---|---|
| Data dodania do BaDAP | 2024-11-20 |
| DOI | 10.1007/978-3-031-54820-8_19 |
| Rok publikacji | 2024 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Czasopismo/seria | Lecture Notes in Networks and Systems |
Abstract
Image fusion is an important task in computer vision, aiming to combine information from multiple modalities to enhance overall perception and understanding. This paper presents an innovative approach to image fusion, specifically focusing on the fusion of RGB and thermal image embeddings to enhance object recognition and detection performance. To achieve this, we introduce two key components, FusionConv and SepThermalConv layers to the YOLO object detection network, as well as modified FusionC3 layer. The FusionConv layer effectively integrates RGB and thermal image features by leveraging multimodal embeddings with use of fusion parameter. Similarly, the SepThermal Conv layer optimizes the processing of thermal information by incorporating separate branches for enhanced representation. Extensive experiments conducted on a custom dataset demonstrate significant performance gains achieved by our fusion method compared to using individual modalities in isolation. Our results highlight the potential of multimodal fusion techniques to improve object detection and perception of complex scenes by effectively combining RGB and thermal images.