Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging by Zirak Khan, Seung-Chul Yoon, Suchendra M. Bhandarkar

“…Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. …”
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Performance-Oriented and Sustainability-Oriented Design of an Effective Android Malware Detector by Sana Qadir, Amna Naeem, Mehdi Hussain, Huma Ghafoor, Aisha Hassan Abdalla Hashim

“…Effective Android malware detection is a complex problem because of the rapidly-evolving, complicated, and diverse nature of malware. …”
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The coupling of a high-efficiency aerosol collector with electrospray ionisation–Orbitrap mass spectrometry as a novel tool for real-time chemical characterisation of fine and ultr... by Y.-S. Lau, Z. Ristovski, B. Miljevic

“…However, a real-time molecular-level characterisation of aerosols remains challenging due to the complex nature of their chemical composition. The current study constructed an instrumental system for the real-time chemical characterisation of aerosol particles. …”
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BRA-YOLOv7: improvements on large leaf disease object detection using FasterNet and dual-level routing attention in YOLOv7 by Rong Ye, Rong Ye, Quan Gao, Quan Gao, Tong Li, Tong Li

“…In the Yunnan region, where the climate is suitable for tea cultivation, tea leaf diseases are small, scattered, and vary in scale, making their detection challenging due to complex backgrounds and issues such as occlusion, overlap, and lighting variations. …”
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CoDAC: Autonomous Obstacle Avoidance Optimization for Unmanned Surface Vehicle Clusters via Multi-Modal Dynamic Perception and Collaborative Community Detection by Youhong Li, Jiawei Ye, Le Gao, Min Cai

“…Second, an incremental dynamic community detection mechanism achieves adaptive task group partitioning for clusters, substantially reducing communication loads and computational complexity while ensuring high-efficiency collaboration at scale. …”
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Enhancing Intelligent Road Target Monitoring: A Novel BGS-YOLO Approach Based on the YOLOv8 Algorithm by Xingyu Liu, Yuanfeng Chu, Yiheng Hu, Nan Zhao

“…This integration overcomes the limitations in feature extraction and recognition found in existing target detection algorithms. Following this, this paper introduces the Global Attention Module (GAM), which markedly improves the efficiency and accuracy of extracting key target information in complex data environments. …”
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Multi-Dimensional Anomaly Detection and Fault Localization in Microservice Architectures: A Dual-Channel Deep Learning Approach with Causal Inference for Intelligent Sensing by Suchuan Xing, Yihan Wang, Wenhe Liu

“…Modern data centers face increasing complexity with distributed microservice architectures, making anomaly detection and fault localization challenging yet critical. …”
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STRUCTURAL GLOBAL SENSITIVITY METHOD BASED ON PARTIAL DERIVATIVE WHOLE DOMAIN INTEGRAL by TU LongWei, LIU Jie, LIU GuangZhao, ZHANG Zheng

“…Numerical example 2 illustrates the validity of the proposed method for complex high-dimensional model. Engineering example demonstrates the applicability and effectiveness of the present method for complex engineering structure problems.…”
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Advanced Cotton Boll Segmentation, Detection, and Counting Using Multi-Level Thresholding Optimized with an Anchor-Free Compact Central Attention Network Model by Arathi Bairi, Uma N. Dulhare

“…There are limited techniques developed to segment, detect, and count cotton bolls precisely. This analysis identified several limitations and issues with these techniques, including their complex structure, low performance, time complexity, poor quality data, and so on. …”
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Investigation of the pathogenic potential and the possibility of cross-species transmission of H5 avian influenza viruses detected on the territory of the Russian Federation in 201... by Nikolay G. Zinyakov, Alena D. Grekhneva, Artem V. Andriyasov, Evgeniya V. Ovchinnikova, Nelli A. Guseva, Anton A. Kozlov, Zoya B. Nikonova, Pavel D. Zhestkov, Dmitry B. Andreychuk, Ilya A. Chvala

“…The rapid evolution of highly pathogenic avian influenza (HPAI) viruses through antigenic drift and reassortment can lead to enhanced replication efficiency and cross-species transmission to mammals, as evidenced by recent outbreaks in various animal populations. …”
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Hydrodynamic performance of a novel suturelessprosthetic aortic valve by K. Yu. Klyshnikov, E. A. Ovcharenko, Yu. A. Kudryavtseva, L. S. Barbarash

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Structural Damage Detection Using an Unmanned Aerial Vehicle-Based 3D Model and Deep Learning on a Reinforced Concrete Arch Bridge by Mary C. Alfaro, Rodrigo S. Vidal, Rick M. Delgadillo, Luis Moya, Joan R. Casas

“…These networks are effective in detecting complex patterns, improving the accuracy and efficiency of damage identification based on simple visual inspection. …”
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Brain Tumor Detection and Prediction in MRI Images Utilizing a Fine-Tuned Transfer Learning Model Integrated Within Deep Learning Frameworks by Deependra Rastogi, Prashant Johri, Massimo Donelli, Lalit Kumar, Shantanu Bindewari, Abhinav Raghav, Sunil Kumar Khatri

“…This result underscores its capability in high-precision brain tumor detection. The study concludes that fine-tuned deep transfer learning architectures, particularly Xception, significantly improve the accuracy and efficiency of brain tumor diagnosis. …”
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Gradual Variation-Based Dual-Stream Deep Learning for Spatial Feature Enhancement With Dimensionality Reduction in Early Alzheimer’s Disease Detection by Najmul Hassan, Abu Saleh Musa Miah, Taro Suzuki, Jungpil Shin

“…However, existing approaches face challenges in achieving good performance due to difficulties in capturing complex spatial features and handling high-dimensional data. …”
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Wheat Soil-Borne Mosaic Virus Disease Detection: A Perspective of Agricultural Decision-Making via Spectral Clustering and Multi-Indicator Feedback by Xue Hou, Chao Zhang, Yunsheng Song, Turki Alghamdi, Majed Aborokbah, Hui Zhang, Haoyue La, Yizhen Wang

“…By using the WSBM dataset collected in 2017–2018 from Walla Walla Valley, Oregon/Washington State border, the United States of America, and performing data augmentation for validation, along with comparative experiments and sensitivity analysis, this study demonstrates that the AI-driven LSGDM model integrating enhanced spectral clustering and ADISs-MGRS feedback mechanisms outperforms traditional models in terms of consensus efficiency and decision robustness. This provides valuable support for multi-party decision making in complex agricultural contexts.…”
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Relational Data Cleaning Meets Artificial Intelligence: A Survey by Jingyu Zhu, Xintong Zhao, Yu Sun, Shaoxu Song, Xiaojie Yuan

“…., statistics, constraints, and clusters, have been extensively studied, with interpretability and efficiency. Recently, considering the strong capability of modeling complex relationships, artificial intelligence (AI) techniques have been introduced into the data cleaning field. …”
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Algorithms for the visual analysis of an environment by an autonomous mobile robot for area cleanup by M. E. Beliakov, S. A. K. Diane

“…One of the key components of such a complex comprises a vision system for detecting and interacting with target objects. …”
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Surface Charge Transfer Enhanced Cobalt‐Phthalocyanine Crystals for Efficient CO2‐to‐CO Electroreduction with Large Current Density Exceeding 1000 mA cm−2 by Tengyi Liu, Di Zhang, Yutaro Hirai, Koju Ito, Kosuke Ishibashi, Naoto Todoroki, Yasutaka Matsuo, Junya Yoshida, Shimpei Ono, Hao Li, Hiroshi Yabu

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Improved crop row detection by employing attention-based vision transformers and convolutional neural networks with integrated depth modeling for precise spatial accuracy by Hassan Afzaal, Derek Rude, Aitazaz A. Farooque, Gurjit S. Randhawa, Arnold W. Schumann, Nicholas Krouglicof

“…This research presents a novel framework that integrates deep learning, precision agriculture, and depth modeling to detect crop rows and spatial information accurately. …”
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BREAST-RANKNet: a fuzzy rank-based ensemble of CNNs with residual learning for enhanced breast cancer detection from ultrasound and mammogram images by Sohaib Asif, Lingying Zhu, Dane Yan, Luman Xu, Zhengqiu Huang, Haimin Xu, Ruxuan Yan, Linghong Cai, Changfu Zheng, Jiamei Lin, Enyu Wang

“…The results demonstrate BREAST-RANKNet’s potential as a robust, efficient tool for early BC detection across diverse datasets.…”
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