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Learning Loss for Active Learning in Depth Reconstruction Problem
P. 000115–000120.
Makarov I., Guschenko-Cheverda I.
Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854
Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...
Added: September 21, 2026
Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., , in: Pattern Recognition. ICPR 2024 International Workshops and Challenges.: Cham: Springer, 2025. P. 308–320.
This research explores an innovative approach to enhancing the accuracy of detecting small microorganisms in complex microscopic environments. Our study introduces a streamlined, hybrid image pre-processing model specifically designed to address the challenges of identifying diplococci in live microscopy of dynamic samples. By integrating pre-defined filtering techniques with predictive adjustments for optimal applicability, our method ...
Added: September 21, 2026
Cham: Springer, 2026.
computer vision ...
Added: September 19, 2026
Aleksei Samarin, Aleksei Toropov, Dzestelova A. et al., , in: Proceedings of the 36th Conference of Open Innovations Association FRUCT, Helsinki, Finland, 30 October - 1 November 2024Vol. 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.: Helsinki: 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
Helsinki: FRUCT Oy, 2025.
Added: September 19, 2026
Helsinki: FRUCT Oy, 2026.
Added: September 19, 2026
Ravedovskaya U., Didenko A., Филатова А. А., Journal of Teaching English for Specific and Academic Purposes 2025 Vol. 13 No. 3 P. 529–538
Emergence of generative artificial intelligence (GenAI) is revolutionizing teaching and evaluation in higher education. Early adopters have already demonstrated how large language model (LLM) conversational agents can serve as on-demand tutors, yet empirical evidence regarding their effectiveness in facilitating conceptual learning in non-computational domains is scant. Based on constructivist learning theory, this paper presents a ...
Added: September 18, 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
Slivnitsin P., Mylnikov L., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
Pikul A. S., Безопасность информационных технологий 2024 Т. 31 № 4 С. 116–127
This article explores the potential use of modern computer vision architectures for the task of deepfake detection. The following architectures are considered: EfficientNet, Vision Transformer (ViT), VisionLSTM (ViL), Vision KAN, and Mamba Vision. The novelty of the approach lies in the application and comparison of these architectures, as well as their combination into paired ensembles ...
Added: December 12, 2025
[б.и.], 2026.
The Winter Conference on Applications of Computer Vision is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers. ...
Added: November 24, 2025
Dalian: IEEE, 2025.
The increasing complexity of modern software development necessitates intelligent, automated security analysis frameworks that can effectively pay attention of human on high-risk software releases. This paper introduces a Multi Agent System (MAS) framework designed to enhance the security assessment process by leveraging artificial intelligence (AI) and intelligent computing for real-time release analysis. The proposed system ...
Added: November 3, 2025
- Р. М., International Journal of Information Technology (Singapore) 2024 Article 1
Added: October 1, 2025
Slastnikov S., Petr Rybakov, Matvei Antonov et al., , in: 24th International Conference, NEW2AN 2024, and 17th Conference, ruSMART 2024, Marrakesh, Morocco, December 11–12, 2024, Proceedings, Part I. Internet of Things, Smart Spaces, and Next Generation Networks and Systems. (LNCS, volume 15554)* 1.: Cham: Springer, 2025. P. 11–18.
An algorithmic and architectural solution is presented for the Search And Rescue (SAR) problem in open areas using image data from UAVs in real time. The solution is an original software and hardware complex that includes a UAV, on-board deployed machine vision application with a novel object detection model and a transmitter to send coordinates ...
Added: June 11, 2025
Springer, 2025.
The multi-volume set LNCS 15623 until LNCS 15646 constitutes the proceedings of the workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024, which took place in Milan, Italy, during September 29–October 4, 2024.
These LNCS volumes contain 574 accepted papers from 53 of the 73 workshops. The list of ...
Added: June 1, 2025
Generation of Artificial Images of Cross Sections of WC/Co Composite Alloys Using Diffusion Networks
Kagramanyan D., Shchur L., Lobachevskii Journal of Mathematics 2025 Vol. 46 No. 3 P. 1315–1321
The study of statistical properties of microstructures of composite materials is carried out by analysing microphotographs of material cuts. The obtained two-dimensional structure represents cuts of composite elements, the geometrical properties of which can be studied by computer vision methods. Hundreds of micro-images can be collected from one microstructure, which allows to study statistical properties ...
Added: January 13, 2025
Springer, 2024.
Added: December 9, 2024
Kseniia Prokudina, Mikhail Skriplyonok, Alexander Vostrikov, , in: 2024 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), 20-24 May 2024.: IEEE, 2024. P. 865–869.
Added: November 26, 2024
Springer, 2024.
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024.
The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal ...
Added: November 26, 2024
Sergeev A., Minchenkov V., Soldatov A. et al., / Cornell University. Серия Computer Science "arxiv.org". 2024. № 2411.10150.
Various technologies, including computer vision models, are employed for the automatic monitoring of manual assembly processes in production. These models detect and classify events such as the presence of components in an assembly area or the connection of components. A major challenge with detection and classification algorithms is their susceptibility to variations in environmental conditions ...
Added: November 23, 2024