?
Application of Neural Networks to Searching for Optical Transients in Astronomical Images Using the Subtraction Method
Pattern Recognition and Image Analysis. 2024. Vol. 34. P. 870–876.
Shekotihin E. A., N. S. Pankov, A. S. Pozanenko, S. O. Belkin
With the beginning of a new gravitational-wave era in astronomy and astrophysics, the problem of identification of gamma-ray bursts optical counterparts is becoming more relevant than ever before. The application of existing methods for identifying transients, in particular image subtraction, is complicated by several factors; the main ones are the variability of observation conditions and the variability of other sources not related to the desired counterpart, as well as the possible absence of reference images from the observatory at which the search is being conducted. This paper examines the results of using deep image prior neural network to translation images from the Pan-STARRS survey to images from the AS-32 telescope of the Abastumani Astrophysical Observatory for the purpose of their subsequent subtraction for the identification and photometry of optical transients. Using examples of fragments of images of the M82 galaxy, the potential of the deep prior approach is demonstrated for both detection of transient events in M82 and for their flux estimation.
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 10 Article 330
Automated microscopic image analysis is essential for quantitative microbiology, yet manual acquisition and generic recognition models struggle with morphological variability and scene artifacts. We address both ends of this pipeline. First, we present a low-cost, open-source acquisition system, based on an Arduino UNO R3 microcontroller and NEMA 17 stepper motors, that automates focusing, magnification, and ...
Added: October 14, 2026
Mamedov I., Fofanov M., Lukianchenko P. et al., IEEE Access 2026 No. 14 P. 26662–26671
DreamBooth-style personalization, which often relies on one or a few images, can memorize context (background, pose, lighting) rather than learning the subject’s identity, thereby reducing fidelity and limiting prompt-driven edits. P-LoRA (Probability LoRA) is introduced as a training-time modification that biases diffusion timestep sampling and utilizes importance weights, ensuring that the overall objective remains unchanged. ...
Added: October 14, 2026
Springer, 2026.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XIV International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2025). The carefully selected papers cover ...
Added: October 13, 2026
Springer, 2026.
This book offers a comprehensive overview of the latest research, innovations, and practical applications in the field of sustainability, with a focus on construction materials and their use in building and civil engineering structures. As an outcome of the 3rd International Conference on Sustainability: Developments and Innovations (ICSDI 2026), this book presents a selection of ...
Added: October 13, 2026
Dmitriev A., Kornilov V., Batienkov R., Lecture Notes in Civil Engineering 2026 Vol. 886 P. 249–255
Numerous studies have provided compelling evidence that the probability distribution of avalanche sizes follows a power law, and that 1/f noise is present in the stochastic dynamics of landslides. We present a theoretical explanation of these phenomena within the framework of self-organized criticality theory, proposing a discrete-time model in the form of a sandpile cellular ...
Added: October 13, 2026
Dmitriev A., Shulman I., Lebedev A., Studies in Computational Intelligence 2026 Vol. 1265 P. 266–273
A discrete-time model is presented for the self-organization of the X/Twitter social network to the edge of a phase transition, characterized by avalanche-like propagation of information in the network. The model is based on the analogy between the critical dynamics of the X social network and sandpile cellular automata with Manna rule on the Chung-Lu ...
Added: October 13, 2026
Arutyunov K., Kharitonov I. A., Petrosyants K. O., JETP Letters 2026 Vol. 124 No. 6 P. 1–16
Superconducting properties of metallic micro- and nanowires can be entirely different from those of bulk superconductors. Of particular interest is the nonequilibrium current-induced state of a quasi-one-dimensional superconducting channel. The most interesting phenomenon here is the stepped I–V characteristic, explained by a process known as phase slip center activation. If the origin of such step-like ...
Added: October 13, 2026
Makarov D. M., Kalikin N., Fashchevsky K. A. et al., Electrochimica Acta 2026 Vol. 579 Article 150159
Machine learning (ML) has become a powerful tool for accelerating the development of carbon-based supercapacitors;
however, most published models assume that a single predictive framework can describe both conventional
porous carbons and hybrid carbon electrodes. Here, we test this assumption using a comprehensive
benchmark dataset and an extended literature-curated dataset enriched with synthesis- and electrolyte-related
descriptors. Three ML algorithms ...
Added: October 13, 2026
Tsyrulnikov M. D., Gayfulin D. R., Svirenko P. I. et al., Russian Meteorology and Hydrology 2024 Vol. 49 P. 638–648
A brief description of the system functioning at the Hydrometcenter of Russia for operational assimilation of meteorological observations and results of the work on its development are given. The main direction of its development is creating an original ensemble variational data assimilation system using neural network modeling techniques. Originality of the system consists in a ...
Added: October 4, 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
Vasilev A., Kapitanov A., Roman Solovyev et al., PeerJ Computer Science 2026 Vol. 12 Article 3724
This article introduces MinMAE, a novel activation calibration method for Post-Training Quantization (PTQ) that significantly reduces accuracy loss in Convolutional Neural Networks (CNN). Motivated by the need for high-fidelity quantization without costly retraining, MinMAE directly minimizes the Mean Absolute Error (MAE) between original and dequantized activations, making it robust to outliers that degrade standard methods. ...
Added: May 3, 2026
Solovyev Roman A., Telpukhov Dmitry, Shafeev I. et al., Technologies 2026 Vol. 14 No. 3 Article 169
With the continuous scaling of semiconductor design technologies, evaluating static IR drop has become a critical bottleneck in the physical synthesis flow. This paper presents a machine learning-based framework that transforms the power delivery network (PDN) analysis problem into an image-to-image translation task using a U-Net architecture with MaxViT and EfficientNet encoders. By implementing a ...
Added: May 3, 2026
Kirsanova E., Pakshin P., Право и экономика 2026 № 3 (456) С. 26–34
The article examines the legal regime of intellectual property created by artificial intelligence. Changes to the existing legal framework towards recognizing artificial intelligence as a legal entity would violate the rationale and fundamental principles of the intellectual property rights system. This article provides an overview of different views on the rationale for granting copyright to ...
Added: April 28, 2026
Pakshin P., Legal Issues in the Digital Age 2026 Vol. 7 No. 1 P. 32–48
Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the ...
Added: March 31, 2026
Semenikhin T., Kornilov M., Pruzhinskaya M. et al., , in: 26th International Conference, DAMDID/RCDL 2024, Nizhny Novgorod, Russia, October 23–25, 2024, Revised Selected Papers. Data Analytics and Management in Data Intensive Domains. (CCIS, volume 2641).: Springer, 2026. P. 211–219.
We considered two fundamentally different approaches to real-bogus classification within the Zwicky Transient Facility survey data. The first approach is based on neural networks that take sequences of object images as input. The second approach uses features extracted from light curves and classical machine learning methods. Several models for both approaches were tested. Quality metrics ...
Added: March 11, 2026
Dzhanashia K., Evsyutin O., Applied Soft Computing Journal 2026 Vol. 186 Article 114125
Watermarking is a key tool in combating unauthorized content distribution, but its effectiveness is often challenged by the wide range of communication channels that can degrade or remove the watermark. We propose a block neural network-based watermarking scheme for digital images that is robust against diverse transmission channels, including compression, pre-processing, and digital-to-analog conversions such ...
Added: October 31, 2025
Teplova T., Sokolova T., Kissa D. et al., Журнал Новой экономической ассоциации 2026 Т. 70 № 1 С. 157–190
This study is the first attempt to apply Explainable Artifi cial Intelligence (ХAI) to reveal the relationship of different Environmental, Social and Governance (ESG) metrics of stock issuers on downside risk in the Russian market. The methodology is based on the two-stage approach, i. e., neural networks with dense layers and the Shapley values from ...
Added: October 17, 2025
Pakshin P., Законодательство 2026 № 9 С. 27–33
Legislators face a choice: recognize artificial intelligence as a sui generis legal entity or replace the creativity criterion with an investment criterion. The author analyzes legal frameworks, doctrine, and case law and believes the latter option is the preferable solution de lege lata. ...
Added: September 7, 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
Pakshin P., Legal Issues in the Digital Age 2025 Vol. 6 No. 3 P. 52–76
The development of Artificial Intelligence (AI) is challenging the traditional legal view of intellectual property. The subject of present research is the justification of the necessity of legal protection of the results of intellectual activity created by AI. The main risk of using AI in the creation of a work is the impossibility of legal ...
Added: May 13, 2025
Makovkin S., Kozinov E., Ivanchenko M. et al., Scientific Reports 2022 Vol. 12 No. 1 P. 0
Recent in vitro and in vivo experiments demonstrate that astrocytes participate in the maintenance of cortical gamma oscillations and recognition memory. However, the mathematical understanding of the underlying dynamical mechanisms remains largely incomplete. Here we investigate how the interplay of slow modulatory astrocytic signaling with fast synaptic transmission controls coherent oscillations in the network of ...
Added: April 9, 2025
Джейранян А. Д., Plaksin M. A., В кн.: Экономика 5.0: коллективный интеллект и развитие: материалы VIII Пермского экономического конгресса (г.Пермь, ПГНИУ, 1–2 февраля 2024 г.).: Пермь: ПГНИУ, 2024. С. 83–92.
The article evaluates the possibility of using currently publicly available generative artificial intelligence systems to organize group examination of software projects. The formulation of requests to chatbots (instructs, prompts) is proposed, which are designed to ensure that the necessary information is received. ...
Added: February 17, 2025
Dushakova I., Душакова Н., Мониторинг общественного мнения: Экономические и социальные перемены 2024 № 5 С. 123–141
The article examines the perception and practices of using generative artificial intelligence in religious communities in Russia within the theoretical framework of the social construction of technology (SCOT). The study’s main objective is to identify the interpretive flexibility of generative AI as a technological artifact in different Orthodox communities in Russia (followers of the Russian Orthodox Church ...
Added: January 20, 2025
Derkach D., Hushchyn M., Samorodova E. et al., Astronomical Society of the Pacific: Conference Series 2024 Vol. 535
In this study, we apply shallow neural networks, bayesian neural networks, and normalizing flows to approximate light curves of astronomical objects. The study shows that the approximation quality of the proposed methods outperform the existing ap- proaches based on Gaussian processes. We assess the quality of solution using two physics-motivated analyses: supernovae type Ia classification ...
Added: January 8, 2025