?
Real-time detection of hogweed: UAV platform empowered by deep learning
IEEE Transactions on Computers. 2021. Vol. 70. No. 8. P. 1175–1188.
Menshchikov A., Shadrin D., Prutyanov V., Lopatkin D., Sosnin S., Tsykunov E., Iakovlev E., Somov A.
The Hogweed of Sosnowskyi (lat. Heracleum sosnowskyi) is poisonous for humans, dangerous for farming crops, and local ecosystems. This plant is fast-growing and has already spread all over Eurasia: from Germany to the Siberian part of Russia, and its distribution expands year-by-year. In-situ detection of this harmful plant is a tremendous challenge for many countries. Meanwhile, there are no automatic systems for detection and localization of hogweed. In this work, we report on an approach for fast and accurate detection of hogweed. The approach includes the Unmanned Aerial Vehicle (UAV) with an embedded system on board running various Fully Convolutional Neural Networks (FCNN). We propose the optimal architecture of FCNN for the embedded system relying on the trade-off between the detection quality and frame rate. We propose a model that achieves ROC AUC 0.96 in the hogweed segmentation task, which can process 4K frames at 0.46 FPS on NVIDIA Jetson Nano. The developed system can recognize the hogweed on the scale of individual plants and leaves. This system opens up a wide vista for obtaining comprehensive and relevant data about the spreading of harmful plants allowing for the elimination of their expansion.
Faizullin R., Mustafin M., Svinin M. et al., , in: 2025 9th International Conference on Information, Control, and Communication Technologies (ICCT-2025).: IEEE, 2025. P. 1–4.
This work addresses the problem of energy-constrained coverage of agricultural fields using a fleet of identical unmanned aerial vehicles (UAVs). Each UAV must complete a spraying mission over a designated area, subject to limited battery capacity. To ensure energy feasibility, static charging stations are deployed along the field’s perimeter. The agricultural field is first partitioned ...
Added: June 23, 2026
Emelyanov A., Sergei Kudriashov, Alena Fenogenova, , in: Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)Vol. 3: System Demonstrations.: Rabat: Association for Computational Linguistics, 2026. Ch. 11 P. 139–153.
Membership Inference Attacks (MIAs) aim to determine whether a specific data point was included in the training set of a target model. Although there are have been numerous methods developed for detecting data contamination in large language models (LLMs), their performance on multimodal LLMs (MLLMs) falls short due to the instabilities introduced through multimodal component ...
Added: May 19, 2026
Ali J. Dayoub, Ehab S. Suleiman, , in: Proceedings of the 2026 8th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE).: IEEE, 2026. Ch. 159 P. 1–5.
Abstract— Urban traffic congestion costs the global economy over $1 trillion annually, necessitating intelligent traffic signal control (ITSC) solutions. Traditional centralized approaches face critical limitations: privacy violations from vehicle trajectory data sharing, prohibitive communication overhead, and scalability challenges in heterogeneous urban environments. This paper presents a federated reinforcement learning (FRL) framework for privacy-preserving traffic signal ...
Added: April 30, 2026
Faizullin R., Imamov N., Tsoy T. et al., , in: Proceedings of the Fifth International Conference on Agriculture Digitalization and Organic Production (ADOP 2025), Volume 1. Robotics in Agriculture. (SIST, volume 453).: Springer, 2026. P. 25 – 34.
This article considers a dual problem of optimizing field coverage while minimizing a soil compaction and managing energy constraints of agricultural robots. The soil compaction in precision agriculture is a major challenge, as mobile robots are becoming increasingly common in field operations. A proposed optimization combines a soil compaction risk assessment with energy-efficient trajectory planning ...
Added: March 17, 2026
Rome: Springer, 2025.
This book constitutes the refereed proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023, held in Rome, Italy, during November 13-15, 2023.
The 9 full papers and 8 short papers included in this book were carefully reviewed and selected from 166 submissions. They were organized in topical sections ...
Added: May 2, 2025
Соловьёв Р. А., Габрушева Т., Ванг В., Image and Vision Computing 2021 Vol. 107 P. 104117–0
We present a novel method for combining predictions in ensembles of different object detection models: weighted boxes fusion. This method significantly improves the quality of the fused predicted rectangles for an ensemble.
We tested the method on several datasets and evaluated it in the context of the Open Images and COCO Object Detection challenges. It helped ...
Added: January 15, 2025
Белокопытов А. С., Kleeva D., Ossadtchi A., , in: Advances in Neural Computation, Machine Learning, and Cognitive Research VIII.: Springer, 2024. P. 317–326.
Added: October 23, 2024
Nikulin A. M., Belousov Y., Svidchenko O. et al., , in: Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track.: PMLR, 2022.
Reinforcement learning competitions advance the field by providing appropriate scope and support to develop solutions toward a specific problem. To promote the development of more broadly applicable methods, organizers need to enforce the use of general techniques, the use of sample-efficient methods, and the reproducibility of the results. While beneficial for the research community, these ...
Added: October 8, 2024
N. S. Kulyasov, N. N. Novik, Klyukin N. D. et al., , in: IOP Conference Series: Earth and Environmental Science. Vol. 548 (2020) 022090. III International Scientific Conference: AGRITECH-III-2020: Agribusiness, Environmental Engineering and Biotechnologies 18-20 June 2020, Krasnoyarsk, Russia.: Institute of Physics Publishing (IOP), 2020. Ch. 2.
The paper is devoted to the analysis of problems and the search for ways to develop precision agriculture in the Russian Federation. The study analyzed the current state of precision agriculture and the level of digitalization of agriculture in the Russian Federation. The main problems for the development of precision agriculture in the Russian Federation ...
Added: September 27, 2024
Rogachev A., Ratnikov F., Computing and Software for Big Science 2024 Vol. 8 No. 1 Article 12
In this paper, we explore the use of Generative Adversarial Networks (GANs) to speed up the simulation process while ensuring that the generated results are consistent in terms of physics metrics. Our main focus is the application of spectral normalization for GANs to generate electromagnetic calorimeter (ECAL) response data, which is a crucial component of ...
Added: July 2, 2024
Cham: Springer, 2024.
This book constitutes revised selected papers from the thoroughly refereed proceedings of the 11th International Conference on Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023.
The 24 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections ...
Added: March 25, 2024
Nikita O. Starodubcev, Nikitin N., Andronova E. et al., Engineering Applications of Artificial Intelligence 2023 Vol. 119 Article 105715
In recent years generative design techniques have become firmly established in numerous applied fields, especially in engineering. These methods are crucial for automating the initial stages of the engineering design of various structures, which reduces the amount of routine work. However, existing approaches are limited by the specificity of the problem under consideration. In addition, ...
Added: March 5, 2024
Zhevnenko D., Kazantsev M., Makarov I., Journal of Industrial Information Integration 2023 Vol. 33 Article 100444
The paper deals with the problem of controlling the state of industrial devices according to the readings of their sensors. The current methods are based on an approach to feature extraction in which the prediction occurs. We propose an interaction method of multiple blocks of different complexity, which aggregate information differently over time, to create ...
Added: February 15, 2024
Kotelnikov A., Baranchuk D., Ivan Rubachev et al., , in: Proceedings of the 40th International Conference on Machine Learning: Volume 202: International Conference on Machine Learning, 23-29 July 2023, Honolulu, Hawaii, USAVol. 202: International Conference on Machine Learning, 23-29 July 2023, Honolulu, Hawaii, USA.: PMLR, 2023. P. 17564–17579.
Denoising diffusion probabilistic models are becoming the leading generative modeling paradigm for many important data modalities. Being the most prevalent in the computer vision community, diffusion models have recently gained some attention in other domains, including speech, NLP, and graph-like data. In this work, we investigate if the framework of diffusion models can be advantageous ...
Added: February 11, 2024
Iakimenko S., В кн.: Современные сетевые технологии: труды 4-й Международной конференции "Современные сетевые технологии" (MoNeTec-2022), 27-29 октября 2022 г., г.Москва (короткие и стендовые доклады).: М.: Издательский отдел факультета ВМК МГУ им. М.В. Ломоносова, 2022. С. 70–76.
The article is devoted to the issues of caching in information-centric networks (ICN), aimed at addressing by the content name and separating information from its producer node. Intra-network caching is one of the main features of ICN, turning them, in fact, into a network of interconnected caches that can accumulate packets in the buffer of ...
Added: December 20, 2022
Moinak Maiti, Ivan Kotliarov, Vitalii Lipatnikov, Blockchain: Research and Applications 2021 Vol. 2 No. 4 Article 100037
The study adopts a single case study approach to bring into conversation, ideas, and views of several scholars on triple entry accounting (TEA). The development of blockchain technology already drives the conscious move towards the TEA. The TEA is currently not being used in any significant way but is in a greater debate whether it ...
Added: September 22, 2022
Begishev V., Moltchanov D., Gaidamaka A. et al., Sensors 2022 Vol. 22 No. 3 Article 977
Unmanned aerial vehicles (UAV) are envisioned to become one of the new types of fifth/sixth generation (5G/6G) network users. To support advanced services for UAVs such as video monitoring, one of the prospective options is to utilize recently standardized New Radio (NR) technology operating in the millimeter-wave (mmWave) frequency band. However, blockage of propagation paths ...
Added: September 15, 2022
Beskopylny A., Shamtsyan M., Springer, 2021.
This book contains original and fundamental research papers in the following areas: engineering technologies for precision agriculture, agricultural systems management and digitalization in agriculture, logistics in agriculture, and other topics. Selected materials of the largest regional scientific event—INTERAGROMASH 2021 conference–included in this book present the results of the latest research in the areas of precision ...
Added: October 31, 2021
Uthayan K. R., Prasad G. L., Mohan V. et al., Computers, Materials and Continua 2022 Vol. 70 No. 3 P. 5161–5177
Recent trends in communication technologies and unmanned aerial vehicles (UAVs) find its application in several areas such as healthcare, surveillance, transportation, etc. Besides, the integration of Internet of things (IoT) with cloud computing environment offers several benefits for the UAV communication. At the same time, aerial scene classification is one of the major research areas ...
Added: October 25, 2021
Guo D., Bai Y., Svinin M. et al., , in: 2022 International Siberian Conference on Control and Communications (SIBCON).: IEEE, 2022. Ch. 9438872 P. 1–5.
Added: October 11, 2021