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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Millimeter-Wave Imaging with Range-Resolved 3D Depth Extraction Using Glow Discharge Detection and Frequency-Modulated Continuous Wave Radar by Arun Ramachandra Kurup, Daniel Rozban, Amir Abramovich, Yitzhak Yitzhaky, Natan Kopeika

“…This work demonstrates the potential of GDD-based 3D MMW imaging as a low-cost, efficient solution for security screening and industrial inspection. …”
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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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MFFCI–YOLOv8: A Lightweight Remote Sensing Object Detection Network Based on Multiscale Features Fusion and Context Information by Sheng Xu, Lin Song, Junru Yin, Qiqiang Chen, Tianming Zhan, Wei Huang

“…This network combines multiscale feature fusion and contextual information to accurately detect objects in RSIs. First, we introduce the lightweight CSP bottleneck with attention module, which utilizes partial convolution calculation and SimAM attention mechanisms to decrease the number of parameters and computational complexity while enhancing feature extraction capabilities. …”
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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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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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Attack scenarios reasoning,hypothesizing and predicting based on capability transition model by TIAN Zhi-hong1, ZHANG Wei-zhe1, ZHANG Yong-zheng2, ZHANG Hong-li 1, LI Yang2, JIANG Wei1

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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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Attack scenarios reasoning,hypothesizing and predicting based on capability transition model by TIAN Zhi-hong1, ZHANG Wei-zhe1, ZHANG Yong-zheng2, ZHANG Hong-li 1, LI Yang2, JIANG Wei1

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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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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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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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A reliable approach for identifying acute lymphoblastic leukemia in microscopic imaging by Mimosette Makem, Levente Tamas, Lucian Bușoniu

“…In this study, we deployed a pre-trained CNN model (MobileNet) that has a small size and low complexity, making it suitable for mobile applications and embedded systems. …”
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Clinical application of metagenomic next-generation sequencing in etiologic diagnosis of severe pneumonia in adults by Zhen-Chuan Xing, Hua-Zheng Guo, Peng Zhen, Ting Ao, Ming Hu

“…The detection efficiencies of different methods were compared and the associated pathogen profiles were analyzed.ResultsAmong the 132 patients, there were 92 males and 40 females, with a total of 52 deaths. …”
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The Historical Evolution and Significance of Multiple Sequence Alignment in Molecular Structure and Function Prediction by Chenyue Zhang, Qinxin Wang, Yiyang Li, Anqi Teng, Gang Hu, Qiqige Wuyun, Wei Zheng

“…Recent breakthroughs in AI, particularly in protein and nucleic acid structure prediction, rely heavily on the accuracy and efficiency of MSAs to enhance remote homology detection and guide spatial restraints. …”
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A Method for Recognizing Dead Sea Bass Based on Improved YOLOv8n by Lizhen Zhang, Chong Xu, Sai Jiang, Mengxiang Zhu, Di Wu

“…Therefore, it is necessary to promptly detect dead fish and take countermeasures. Existing object detection algorithms, when applied to the task of detecting dead sea bass, often suffer from excessive model complexity, high computational cost, and reduced accuracy in the presence of occlusion. …”
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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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Automated Coronary Artery Identification in CT Angiography: A Deep Learning Approach Using Bounding Boxes by Marin Sakamoto, Takaaki Yoshimura, Hiroyuki Sugimori

“…They also highlight the need to refine the approach for complex anatomical variants or calcified plaques. …”
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