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5th doors 2025: Zhytomyr, Ukraine
- Tetiana A. Vakaliuk, Serhiy O. Semerikov:
Proceedings of the 5th Edge Computing Workshop (doors 2025), Zhytomyr, Ukraine, April 4, 2025. CEUR Workshop Proceedings 3943, CEUR-WS.org 2025 - Preface. 1-3
- Nikita S. Prasol, Denys V. Furikhata, Tetiana A. Vakaliuk, Timothy Y. Regenel:
Integration of edge devices and IoT to create a climate monitoring system for plants. 4-19 - Dmytro V. Shevchenko, Bella L. Holub:
Regression analysis as a tool for identifying patterns in atmospheric air monitoring data. 20-27 - Yanan Song, Siwei Wei, Donghua Liu:
GADGN: A dual graph convolutional architecture for traffic flow prediction. 28-41 - Oleksandr Chaban, Eduard Manziuk, Olena Markevych, Sergi Petrovskyi, Pavlo Radiuk:
EMTKD at the edge: An adaptive multi-teacher knowledge distillation for robust cardiac MRI classification. 42-57 - Dmytro I. Shvaika, Andrii I. Shvaika, Dmytro I. Landiak, Volodymyr O. Artemchuk:
Scalable and reliable MQTT messaging: evaluating TBMQ for P2P scenarios. 58-66 - Viktor O. Maliarskyi, Vasyl P. Oleksiuk:
Review of modern tools for edge computing systems quality assurance. 67-80 - Vadim V. Romanuke, Serhii Y. Dementiev, Svitlana Yaremko:
An IoT-based system of mechanizing sport competition motion for perception improvement. 81-96 - Zhicheng Li, Xinlu Zong, Jiaxin Hao, Orest Kochan:
Multi-UAV 3D path planning based on improved sparrow search algorithm. 97-108 - Oleg Kobylin, Oleksandra Putiatina:
Some aspects of real-time image denoising influenced by shot noise and compound Poisson noise. 109-117 - Ihor A. Pilkevych, Mykola P. Romanchuk, Olena M. Naumchak, Dmytro L. Fedorchuk, Leonid M. Naumchak:
Improved model for detecting randomly oriented objects on remote sensing images. 118-126 - Quan Trong The:
Bayesian estimators-based microphone array speech enhancement in adverse environment. 127-136 - Serhiy O. Semerikov, Tetiana A. Vakaliuk, Olga B. Kanevska, Mykhailo V. Moiseienko, Ivan I. Donchev, Andrii O. Kolhatin:
LLM on the edge: the new frontier. 137-161 - Ming Xue:
Studying the efficiency and performance of the vehicle detection method based on feature fusion and attention enhancement. 162-177

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