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Advances in Neural Computation, Machine Learning, and Cognitive Research IX
Vol. 1241.
Springer, Cham, 2026.
computer vision
Chapters
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., , in: Advances in Neural Computation, Machine Learning, and Cognitive Research IXVol. 1241.: Springer, Cham, 2026. P. 34–46.
This study investigates the integration of attention mechanisms within deep learning architectures, specifically targeting the segmentation of bacilli microorganisms in microscopy images. We introduce novel modifications to attention blocks, tailored to address challenges inherent to microscopy imaging, such as blurred boundaries and indistinct microorganism features. Our experimental results demonstrate significant performance improvements compared to baseline ...
Added: September 19, 2026
Springer, Cham, 2026.
Added: September 19, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., Proceedings of the ACM on Management of Data 2026 Vol. 4 No. 1 P. 1–28
Modern knowledge and large volumes of data are increasingly encoded within neural networks, making the task of simplifying their structures and reducing the number of parameters especially relevant, both to improve efficiency and to facilitate deployment in resource-constrained environments. This paper presents a novel approach to neural network compression that addresses redundancy at both the ...
Added: September 19, 2026
FRUCT Oy, 2024.
Added: September 19, 2026
Aleksei Samarin, Aleksei Toropov, Dzestelova A. et al., , in: Proceedings of the 36th Conference of Open Innovations Association FRUCTVol. 36.: FRUCT Oy, 2024. P. 903–911.
In this work, we describe our research aimed at developing classifiers for microbial images (bacilli images) obtained through microscopy of live (non-static) samples. We employed our proposed approach called AutoML, which is based on the automatic generation and analysis of the feature space to create the most optimal descriptors for microscopic images used in their ...
Added: September 19, 2026
FRUCT Oy, 2024.
Added: September 19, 2026
Aleksei Samarin, Aleksei Toropov, Kotenko E. et al., , in: Proceedings of the 37th Conference of Open Innovations Association FRUCTVol. 37.: FRUCT Oy, 2025. P. 278–284.
This study introduces an innovative method for recognizing automatically generated images by utilizing adapted descriptors specifically designed to analyze unique structural and morphological features characteristic of artificially created content. The methodology focuses on analyzing features inherent to image generation processes, ensuring the optimization of descriptors for identifying complex and subtle patterns associated with generative algorithms. ...
Added: September 19, 2026
FRUCT Oy, 2025.
Added: September 19, 2026
Aleksei Samarin, Aleksei Toropov, Nazarenko A. et al., , in: Proceedings of the 39th Conference of Open Innovations Association FRUCTVol. 39.: FRUCT Oy, 2026. P. 253–261.
Commercial facade service classification from streetlevel imagery benefits from multi-branch pipelines that fuse global facade appearance with signboard-centric cues; however, this design increases inference cost and hinders large-scale deployment. We study pruning for a multi-branch facade recognition pipeline with a trainable signboard descriptor and compare unstructured magnitude pruning with structured baselines, including channel pruning and ...
Added: September 19, 2026
FRUCT Oy, 2026.
Added: September 19, 2026
Aleksei Samarin, Kotenko E., Aleksei Toropov et al., , in: ICICT 2026: Proceedings of the 2026 9th International Conference on Information and Computer Technologies.: Association for Computing Machinery (ACM), 2026. P. 155–161.
This study investigates the integration of attention mechanisms within deep learning architectures, specifically focusing on the segmentation of diplococci microorganisms in microscopy images. We introduce novel modifications to attention blocks, tailored to address challenges inherent to microscopy imaging, such as blurred boundaries and indistinct microorganism features. Our experimental results demonstrate significant performance improvements compared to ...
Added: September 19, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 8 P. 1–26
This paper presents a novel method for pruning deep neural networks based on the concept of flow, derived from the continuous modeling of signal propagation across layers. We derive flow functions for fully connected, convolutional, and self-attention architectures, and we propose a new iterative pruning algorithm, Iterative Flow-Aware Pruning (IFAP), that leverages these measures to ...
Added: September 19, 2026
Myachin A. L., Procedia Computer Science 2026 Vol. 287 P. 193–200
We extend the static pattern analysis method to the temporal dimension by introducing a six-type trajectory taxonomy that classifies objects according to the frequency and structure of pattern switches over an observation window of T > 8 periods. For each object, a reference pattern is designated as the most frequently occupied group over the observation ...
Added: September 18, 2026
Kuzyutin D., Smirnova N., Veselkov A., Bulletin of the South Ural State University, Series: Mathematical Modelling, Programming and Computer Software 2026 Vol. 19 No. 3 P. 40–49
We consider spatial dynamic fishery management problem taking into account the resource migration process between an open-access fishing area and no-take marine protected area. The introduced extension of a standard single-criterion fish war game implies that each player aims to maximize simultaneously two performance criteria which present an economic benefit and an environmental conservation goal ...
Added: September 18, 2026
Громов Р. С., Нестеров Р.А., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4 P. 23–44
This paper explores the performance criteria of the newest algorithm for solving the problem of finding shortest paths on a graph from a given vertex – Bounded Multi-Source Shortest Path Algorithm
(BM-SSP). The algorithm was published in 2025 and, as its creators claim, it is asymptotically superior to Dijkstra’s deterministic algorithm. However, in the publication devoted ...
Added: September 18, 2026
Ramos-Soto O., Perez-Zarate E., Ramos-Frutos J. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 7 Article 173
Added: September 18, 2026
Ероховец Николай Юрьевич, Математический сборник 2026 Т. 217 № 5 С. 45–89
Toric topology assigns to each simple convex n-polytope P with m facets an n-dimensional real moment-angle manifold RZP with a canonical action of Zm2=(Z/2Z)m. We consider (not necessarily free) actions of subgroups H⊂Zm2 on RZP. The orbit space N(P,H)=RZP/H carries an action of Zm2/H. For general n we introduce the notion of Hamiltonian C(n,k)-subcomplex in the boundary of an ...
Added: September 17, 2026
Kuninets A., Malygina E., Cryptography and Communications 2026
In this paper, we determine explicit bases for Riemann–Roch spaces associated with various families of elliptic codes. We establish the feasibility and provide exact algorithms for constructing bases of Riemann–Roch spaces corresponding to arbitrary divisors on elliptic curves, including the non-effective case. These results are subsequently applied to derive bases for quasi-cyclic elliptic codes and ...
Added: September 17, 2026
Кузнецов М. Е., Полякова М., Лукьянович В. et al., ФАНУ "Востокгосплан", 2026.
Обзор международных практик развития робототехники и искусственного интеллекта и оценка возможностей их применения в условиях России, в первую очередь для Дальнего Востока и Арктической зоны РФ ...
Added: September 16, 2026
Lebedev O. B., Черкасов Р. И., Известия ЮФУ. Технические науки 2025 № 5(247) С. 254–276
This paper considers the application of artificial intelligence technologies, in particular computer vision, in visual information processing systems. A comprehensive analysis of neural network approaches to solving computer vision problems is carried out, including systematization of key types of problems: image classification, object detection and semantic segmentation. The architectural principles of convolutional neural networks are ...
Added: September 10, 2026
Lebedev O. B., Шмелева А. Г., Гежа Н. С., Информатика и автоматизация (Труды СПИИРАН) 2026 Т. 25 № 3 С. 720–750
This paper describes the development of a neural network model for automated analysis of medical data in electrophysiology based on deep learning methods. The relevance of this work stems from the growing need to improve the objectivity, speed, and accuracy of processing complex spatiotemporal signals, such as ECG or EEG. Convolutional neural networks (CNNs), which ...
Added: September 10, 2026
Зуенко Д. О., Trofimova E., Хайдарова И., IEEE Access 2026 Vol. 14 P. 121339–121357
Oil spill segmentation in Synthetic Aperture Radar (SAR) images is limited by noisy annotations in publicly available datasets and by architectural choices that interact with label quality in opposing directions. First, we introduce a manually refined version of the Deep-SAR Oil Spill (SOS) dataset, in which 36.25% of masks are corrected for false positives, missed ...
Added: September 7, 2026
Kaznacheev P. A., Indakov G. S., Podymova N. B. et al., Izvestiya - Physics of the Solid Earth 2026 Vol. 61 P. 68–80
The paper discusses methods for estimating the grain size of polycrystalline materials based on the analysis of optical microscopic images, as well as the possibility of applying these methods to the analysis of rock textures. A comparison of the results obtained using several methods on a single sample of metamorphosed sandstone from the Northern Ladoga ...
Added: August 31, 2026
Gamberov T., Safin R., Chebotareva E. et al., , in: 2025 9th International Conference on Information, Control, and Communication Technologies (ICCT-2025).: IEEE, 2025. P. 1–5.
Digital human models (DHM) for virtual environments allow a cost-effective and reproducible evaluation of computer vision algorithms that are employed in robotics, e.g., human detection, tracking and following. Yet, many popular robotics simulators do not achieve a reasonable level of realism and diversity required to rigorously test such algorithms under varying conditions. This paper introduces ...
Added: June 23, 2026
Makarov N., Savchenko A., Zemtsova I. et al., Scientific Reports 2025 Vol. 15 Article 26641
The grey wolf (Canis lupus) is a pivotal species for ecological studies. As a key participant in ecosystem
processes, it also serves as a model for investigating social structure formation and ecological
adaptation. However, the species’ complex social behavior, spatial dynamics, and expansive habitats
make monitoring and population assessments across large areas particularly challenging. In recent
years, audio traps ...
Added: June 16, 2026