A Study on Lightweight Object Detection in Thermal Images and Its Recent Advances
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3817-5_24
Reference38 articles.
1. Krišto M, Ivasic-Kos M, Pobar M (2020) Thermal object detection in difficult weather conditions using YOLO. IEEE Access 8:125459–125476
2. Bustos N et al. (2023) A systematic literature review on object detection using near infrared and thermal images. Neurocomputing 126804
3. Akkaya IB, Altinel F, Halici U (2021) Self-training guided adversarial domain adaptation for thermal imagery. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
4. Kera SB, Tadepalli A, Jennifer Ranjani J (2023) A paced multi-stage block-wise approach for object detection in thermal images. The Visual Computer 39.6:2347–2363
5. Vs V, Poster D, You S, Hu S, Patel VM (2022) Meta-UDA: unsupervised domain adaptive thermal object detection using meta-learning. In: 2022 IEEE/CVF winter conference on applications of computer vision (WACV), Waikoloa, HI, USA, pp 3697–3706. https://doi.org/10.1109/WACV51458.2022.00375
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