Enhancing Online Fraud Detection: Leveraging Machine Learning and Behavioral Indicators for Improved Accuracy and Real-Time Detection by Shaha Prasad, Gavekar Vidya

“…The study also highlights the importance of feature selection, class imbalance handling, and real-world applicability by discussing computational efficiency and deployment challenges. …”
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MA-YOLO: A Pest Target Detection Algorithm with Multi-Scale Fusion and Attention Mechanism by Yongzong Lu, Pengfei Liu, Chong Tan

“…To address the high computational complexity and inadequate feature representation in traditional convolutional networks, this study proposes MA-YOLO, an agricultural pest detection model based on multi-scale fusion and attention mechanisms. …”
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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

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OPTISTACK: A Hybrid Ensemble Learning and XAI-Based Approach for Malware Detection in Compressed Files by Khaled Mahmud Sujon, Rohayanti Binti Hassan, M. Abdullah-Al-Wadud, Jia Uddin

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LiSA-MobileNetV2: an extremely lightweight deep learning model with Swish activation and attention mechanism for accurate rice disease classification by Yongqi Xu, Dongcheng Li, Changcheng Li, Zheming Yuan, Zhijun Dai

“…In the context of intelligent agriculture in China, rapid and accurate identification of crop diseases is essential for ensuring food security and improving crop yield. Although lightweight convolutional neural networks (CNNs) are widely adopted for plant disease recognition due to their computational efficiency, they often suffer from limited feature representation and classification accuracy. …”
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A survey of data-driven fault-diagnosis methods for large-scale industrial production processes by Qianxiang YU, Qing LI, Linlin LI, Yixuan WANG

“…The usual fault-diagnosis methods for large-scale systems rely on centralized sensor network monitoring. Centralization necessitates consolidated data processing, which can create immense computational stress. …”
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Constructing segmentation method for wheat powdery mildew using deep learning by Hecang Zang, Hecang Zang, Congsheng Wang, Qing Zhao, Qing Zhao, Jie Zhang, Jie Zhang, Junmei Wang, Guoqing Zheng, Guoqing Zheng, Guoqiang Li, Guoqiang Li

“…Finally, in the deep bottleneck of Swin-Unet network, ResNet network layers are used to increase the expressive power of feature. …”
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A hybrid data-driven method for voltage state prediction and fault warning of Li-ion batteries by Yufeng Huang, Xuejian Gong, Zhiyu Lin, Lei Xu

“…Firstly, an 1DCNN module is introduced to extract voltage-related multi-dimension features. Secondly, a Bi-LSTM module is used to learn long-term dependence relationships among fused features while integrating a self-attention mechanism. …”
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Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption by Jeyamala Chandrasekaran, S. J. Thiruvengadam

“…Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. …”
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Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

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DMN-YOLO: A Robust YOLOv11 Model for Detecting Apple Leaf Diseases in Complex Field Conditions by Lijun Gao, Hongwu Cao, Hua Zou, Huanhuan Wu

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Multi-View Cluster Structure Guided One-Class BLS-Autoencoder for Intrusion Detection by Qifan Yang, Yu-Ang Chen, Yifan Shi

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Improving internet of vehicles research: A systematic preprocessing framework for the VeReMi datasetZenodo by Aparup Roy, Debotosh Bhattacharjee, Ondrej Krejcar

“…The optimized dataset is well-suited for ITS and IoV applications, such as anomaly detection and network security, underscoring the crucial role of preprocessing in overcoming real-world constraints and enhancing model performance.…”
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Fractional Artificial Protozoa Optimization Enabled Deep Learning for Intrusion Detection and Mitigation in Cyber-Physical Systems by Shaik Abdul Rahim, Arun Manoharan

“…CPSs are gradually growing and utilized in important infrastructure and industries for attaining smart grid, smart transportation, and smart healthcare, which assists governments and citizens. Nevertheless, the network and wireless communication technology creates high complexity, and the intelligence and dynamic of network intrusions make CPS more insecure to network intrusions and provide more critical threats to human life and national security. …”
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InterAcT: A generic keypoints-based lightweight transformer model for recognition of human solo actions and interactions in aerial videos. by Mubashir Shah, Tahir Nawaz, Rab Nawaz, Nasir Rashid, Muhammad Osama Ali

“…To this end, this paper presents a generic lightweight and computationally efficient Transformer network-based model, referred to as InterAcT, that relies on extracted bodily keypoints using YOLO v8 to recognize human solo actions as well as interactions in aerial videos. …”
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Survey of deep fake audio generation and detection techniques by ZENG Zhiping, ZHANG Xulong, QU Xiaoyang, XIAO Chunguang, WANG Jianzong

“…Subsequently, an in-depth analysis was conducted on both acoustic feature-based and end-to-end model-based fake audio detection strategies, delving into details such as deep acoustic feature detection, pre-trained neural network feature detection, end-to-end model optimization, generalization enhancement techniques, and the enhancement of real-time detection. …”
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Editorial by Teddy Surya Gunawan

“…The most significant representation comes from Electrical, Computer, and Communications Engineering, where numerous works delve into AI, signal processing, secure communications, and sensor networks. …”
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Issues, Challenges, and Solution Options for On-Grid Multi-Microgrid Game Theory: A Systematic Review by Dimas Jalaluddin Ahmad, Nanang Hariyanto, Umar Khayam

“…This connection provides more flexibility in operation and various features, including multi-level interactions beyond peer-to-peer, asymmetric agents, the presence of distribution network operator, support and backup power from the grid, and an energy market pool. …”
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An effective PO-RSNN and FZCIS based diabetes prediction and stroke analysis in the metaverse environment by M. Karpagam, S. Sarumathi, A. Maheshwari, K. Vijayalakshmi, K. Jagadeesh, V. Bereznychenko, R. Narayanamoorthi

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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

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