Titlebook: Information Technologies and Their Applications; Second International Gulchohra Mammadova,Telman Aliev,Kamil Aida-zade Conference proceedin

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障碍物

Ontological Approach to Describing the Interaction of Information Processes in Intelligent Systemsaper discusses in the most detail the lower level related to the interpretation of information processes within the hardware platform. Two approaches to organizing of the such interpretation are considered.

品牌

LANet: Lightweight Attention Network for Medical Image SegmentationiT as a lightweight backbone network with a small number of parameters, facilitating easy training and faster predictive inference. The efficiency of LANet was evaluated using four public datasets: kvasir-SEG, CVC-clinicDB, CVC-colonDB, and the Data Science Bowl 2018. Experimental results demonstrat

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角斗士

Innovative Construction Technologies for Smart Villages: Case Study Karabakhumber of such projects around the world, the level of their theoretical and methodological validity is not sufficient. This paper examines the construction technologies for sustainable smart villages, focusing on innovative energy-efficient engineering systems and measures. The subject of the study

抗生素

Turkish Legal Single-Document Summarizing large amount of information research, articles, documents, books, etc., and the development of Internet technologies, text summarization has become an important tool by extracting the most important parts and clarifying the basic purpose of the text. It is very necessary for lawyers and ordinary ci

有组织

Technologies and Systems for Monitoring the Onset of Accidents at Strategic Constructionial technical facilities. The signaling of the beginning of the latent period of an emergency state is not implemented either. There are no tools for monitoring malfunctions of the railroad bed, or for controlling the beginning of the emergence of various typical malfunctions in the equipment of urb

灌输

Optimizing Feature Distributions for Unsupervised Deep Learning-Based Fabric Defect Detection and Loenges related to overgeneralization due to relying only on the in-distribution, which represents normal samples for training. In this paper, we introduce an improved approach to address overgeneralization issues and augment the accuracy of fabric defect detection and localization. Our approach lever

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