Seal Pipeline: Enhancing Dynamic Object Detection and Tracking for Autonomous Unmanned Surface Vehicles in Maritime Environments by Mohamed Ahmed, Bader Rasheed, Hadi Salloum, Mostafa Hegazy, Mohammad Reza Bahrami, Mikhail Chuchkalov

“…This study addresses the dynamic object detection problem for Unmanned Surface Vehicles (USVs) in marine environments, which is complicated by boat tilting and camera illumination sensitivity. …”
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A Welding Defect Detection Model Based on Hybrid-Enhanced Multi-Granularity Spatiotemporal Representation Learning by Chenbo Shi, Shaojia Yan, Lei Wang, Changsheng Zhu, Yue Yu, Xiangteng Zang, Aiping Liu, Chun Zhang, Xiaobing Feng

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DISCERN: deep single-cell expression reconstruction for improved cell clustering and cell subtype and state detection by Fabian Hausmann, Can Ergen, Robin Khatri, Matteo Marouf, Sonja Hänzelmann, Nicola Gagliani, Samuel Huber, Pierre Machart, Stefan Bonn

“…We show that DISCERN is robust against differences between batches and is able to keep biological differences between batches, which is a common problem for imputation and batch correction algorithms. …”
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Blockchain covert communication scheme based on the cover of normal transactions by Pengkun JIANG, Wenyin ZHANG, Jiuru WANG, Shanyun HUANG, Wanshui SONG

“…With the development of computer technology, the situation of modern network attack and defense is becoming increasingly severe, and the problem of secure transmission of secret information needs to be solved urgently.Covert communication technology embeds secret information into the carrier and transmits the information safely through the covert channel.However, the traditional covert channels face the challenges of data damaging, attack, detection and so on, which cannot meet the higher security requirements.As a public data platform, blockchain can embed secret information under the cover of a large number of transactions.With its tamper proof, anonymity, decentralization and other characteristics, blockchain can well solve the problems of traditional covert channels and achieve secure covert communication.However, the existing blockchain covert communication schemes are limited by low communication efficiency and poor security.How to improve safety and efficiency of covert communication is a research focus of blockchain covert communication.Motivated by this issue, a blockchain covert communication scheme based on the cover of normal transactions was proposed.The hash algorithm was used to build a transmission-free password table to embed secret information without changing any transaction data.Using the elliptic curve feature, transactions with hidden information can be quickly screened out from a large number of transactions, to extract secret information quickly.This scheme improves the security and efficiency of covert communication and has strong portability.Theoretical analysis shows that attackers cannot distinguish between ordinary transactions and special transactions.This scheme has high anti-detection and scalability.Besides, the experimental results of the bitcoin test network show the high efficiency of this scheme.…”
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Tailhook Recognition for Carrier-Based Aircraft Based on YOLO with Bi-Level Routing Attention by Aiguo Lu, Pandi Liu, Jie Yang, Zhe Li, Ke Wang

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High-resolution 2D-DoA sequential algorithm of azimuth and elevation estimation in automotive distributed system of coherent MIMO radars by I. V. Artyukhin

“…Algorithms must be developed to provide high angular resolution and low computational complexity. …”
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MATHEMATICAL MODEL OF COMPLEX PROTECTION OF AN INFOCOMMUNICATION OBJECT BASED ON "PLAYING WITH NATURE" by I. S. Klimenko

“…Theoretical and methodological approaches to the complex protection of info-communication objects, which are based on game theory, determine the relevance and practical significance of the development of mathematical models of real systems in the format offinite matrix games. The algorithm of formalization of protection processes is proposed, which ensures efficient use of resources when detecting possible incidents of violation of the protection system and/or unauthorized access. …”
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Sensor Image, Anomaly Detection Method for Hydroelectric Dam Structure Using Sensors Measurements and Deep Learning by Van-Phuong Ha, Dinh-Van Nguyen, Trong-Chuong Trinh, Duc-Cuong Quach, Van HuyBui

“…To better prevent future disasters, machine-learning algorithms have been employed. Often, these algorithms are trained on historical sensor data to predict future events. …”
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Intelligent agriculture: deep learning in UAV-based remote sensing imagery for crop diseases and pests detection by Hongyan Zhu, Hongyan Zhu, Chengzhi Lin, Chengzhi Lin, Gengqi Liu, Gengqi Liu, Dani Wang, Dani Wang, Shuai Qin, Shuai Qin, Anjie Li, Anjie Li, Jun-Li Xu, Yong He

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DSCW-YOLO: Vehicle Detection from Low-Altitude UAV Perspective via Coordinate Awareness and Collaborative Module Optimization by Qingqi Zhang, Hao Wang, Xinbo Wang, Jiapeng Shang, Xiaoli Wang, Jie Li, Yan Wang

“…This paper proposes an optimized algorithm based on YOLOv11s to address the problem of insufficient detection accuracy of vehicle targets from a drone perspective due to certain scenes involving complex backgrounds, dense vehicle targets, and/or large variations in vehicle target scales due to oblique imaging. …”
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CGA-Net: A CNN-GAT Aggregation Network Based on Metric for Change Detection in Remote Sensing by Huilan Lin, Chunlei Zhao, Rong He, Ming Zhu, Xin Jiang, Yi Qin, Wen Gao

“…Attempting to solve the problems in existing object-level change detection methods, such as ignoring the relationship between dual-branch features, insufficient utilization of feature point information, and unreasonable fusion weight allocation mechanism, this article proposes an object-level change detection network, CGA-Net, based on metric, which combines similarity measurement with the feature extraction and fusion. …”
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A combined feature selection approach for malicious email detection based on a comprehensive email dataset by Han Zhang, Yong Shi, Ming Liu, Libo Chen, Songyang Wu, Zhi Xue

“…We summarize two major challenges in the current field of malicious email detection using machine learning algorithms. (1) Current works on malicious email detection use different datasets and lack a unified and comprehensive open source dataset standard for evaluating detection performance. …”
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Self-Sensing of Piezoelectric Micropumps: Gas Bubble Detection by Artificial Intelligence Methods on Limited Embedded Systems by Kristjan Axelsson, Mohammadhossien Sheikhsarraf, Christoph Kutter, Martin Richter

“…Different types of sensors are used to detect gas bubbles: inline on the fluidic channels or inside the pump chamber itself. …”
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An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion by Kavita Rawat, Trapti Sharma

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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…In modern power systems, insulators, as key components of transmission lines, are crucial for defect detection for the safe operation of power grids. Aiming at the problems of low efficiency of traditional manual detection, the vulnerability of traditional image processing methods to environmental interference, and the insufficient ability of existing deep learning models to detect small target defects under complex backgrounds, this paper proposes an improved target detection model based on YOLOv10n, which is the first time to integrate the spatial channel attention mechanism (SEAttention) with the up-sampling expansion operation (Patch Expanding) in the Neck part of the model. …”
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Polarimetric SAR Ship Detection Using Context Aggregation Network Enhanced by Local and Edge Component Characteristics by Canbin Hu, Hongyun Chen, Xiaokun Sun, Fei Ma

“…However, polarization SAR methods for ship detection still face challenges. The traditional constant false alarm rate (CFAR) detectors face sea clutter modeling and parameter estimation problems in ship detection, which is difficult to adapt to the complex background. …”
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LDDFSF-YOLO11: A Lightweight Insulator Defect Detection Method Focusing on Small-Sized Features by Peng Shen, Keyu Mei, Huiqiong Cao, Yongxiang Zhao, Guoqing Zhang

“…Due to complex environmental conditions, varying viewing angles, and unstable lighting conditions, existing insulator defect detection algorithms still face challenges, including missed detection, false detection, and inadequate adaptability for detecting small-sized defects in UAV captured images. …”
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Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines by Tymochko O., Fustii V., Kolesnyk G., Olizarenko S., Kalashnyk G., Kulish R., Tymoschuk O., Galinskji D.

“…The drone route planning problem was represented by a multi-agent variation of the classical traveling salesman problem and was solved by the ant colony method. …”
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Parameter Estimation of Non-Gaussian Signals for Polarization-Sensitive Augmented Coprime Array: Fourth-Order Cumulant Reduced-Dimensional Capon Algorithm by Meng Yang, Haowei Zeng, Xiaofei Zhang

“…In this paper, we investigate the problem of direction of arrival (DOA) and polarization estimation for non-Gaussian signal in polarization-sensitive augmented coprime array. …”
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Coal Combustion Warning System Based on TDLAS and Performance Research by Zhitao Xie, Guanyu Lin, Jianing Wang, Xi Wang, Weijia Li, Pengbo Li, Hengyuan Kong

“…As the signature gas released before coal combustion, methane’s telemetry accuracy is susceptible to environmental influences, which is a difficult problem that needs to be solved. This article provides a detailed exposition on the application of Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology in the field of gas monitoring, with particular emphasis on its advantages in coal safety detection. …”
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