Enhanced Anomaly Detection in IoT Networks Using Deep Autoencoders with Feature Selection Techniques by Hamza Rhachi, Younes Balboul, Anas Bouayad

“…Compared to some IoT-based anomaly detection models, the experimental results reveal that the suggested model is more efficient at enhancing the accuracy of detecting malicious data. …”
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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…This study presents a novel adaptation of the Hoeffding Adaptive Tree (HAT) classifier with an instance selection algorithm that detects and identifies cyber and non-cyber contingencies in real time to enhance the situational awareness of cyber-physical power systems (CPPS). …”
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Cutting-Edge Phishing Detection Using Novel Features and Hybrid Machine Learning Techniques by Jin Zhang

“…Classification Information Mining (DM) strategies are highly effective tools for identifying and detecting e-banking phishing websites. This study introduces a novel approach to address the challenges and complexities associated with predicting and identifying such websites. …”
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Deep learning-based ensemble stacking for enhanced intrusion detection in IoT-edge platforms by P. R. Chithra Rani, K. Baalaji

“…This research contributes a scalable, efficient, and resource-aware intrusion-detection approach to extending the resilience of IoT-edge systems in distributed computing environments.…”
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A Rotation Target Detection Network Based on Multi-Kernel Interaction and Hierarchical Expansion by Qi Wang, Guanghu Xu, Donglin Jing

“…Through multi-scale feature interaction and direction-aware optimization, MIHE-Net effectively addresses the challenges posed by scale gradation and direction diversity in remote sensing target detection, providing an efficient and feasible solution for high-precision remote sensing target detection.…”
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ABA-IDS: Attention-Based Autoencoder for Intrusion Detection in Assistive Mobility Robotic Network by Daniel Ayo Oladele, Elisha Didam Markus

“…To mitigate these vulnerabilities, researchers have developed machine and deep learning-based intrusion detection systems (IDS). However, these systems often struggle with low feature learning and high model complexity, making them unsuitable for resource-constrained CAN networks. …”
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Semi-supervised anomaly detection from Chlorella vulgaris cultivations using hyperspectral imaging by Salli Pääkkönen, Ilkka Pölönen, Pauliina Salmi

“…More evolved anomaly detection methods are needed to ensure efficient quality control of microalgae cultivations. …”
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Spin-Wheel: A Fast and Secure Chaotic Encryption System with Data Integrity Detection by Luis D. Espino-Mandujano, Rogelio Hasimoto-Beltran

“…This approach exacerbates the complexity in the event of an attack, since the trajectories may come from the same or totally different maps in a non-sequential time order. …”
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Adaptive distributed honeypot detection network for enhanced cybersecurity against DoS and DDoS attacks by V. Selva Kumar, K.R. Mohan Raj, S. Gopalakrishnan, G. Vennila, D. Dhinakaran, P. Kavitha

“…Traditional detection techniques often fall short in addressing the complexities posed by dynamic traffic patterns, diverse attack types, and real-time processing demands. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…While various computer-aided systems have been developed to assist in DR detection, there remains a need for accurate and efficient methods to classify its stages. …”
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Hybrid YOLOv8 and Fast R-CNN for Accurate Schematic Detection in Power Distribution Networks by Aviv Yuniar Rahman, Zuhaina Zakaria

“…Conventional edge detection methods often struggle with the complexity and scale of modern PDNs, while standalone deep learning approaches face challenges in balancing real-time performance and high precision. …”
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MoNetViT: an efficient fusion of CNN and transformer technologies for visual navigation assistance with multi query attention by Liliek Triyono, Liliek Triyono, Rahmat Gernowo, Prayitno

“…Experiments show MoNetViT outperforms other semantic segmentation algorithms in efficiency and effectiveness, particularly in detecting Aruco markers, making it a promising tool to improve navigation aids for the visually impaired.…”
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YOLOLS: A Lightweight and High-Precision Power Insulator Defect Detection Network for Real-Time Edge Deployment by Qinglong Wang, Zhengyu Hu, Entuo Li, Guyu Wu, Wengang Yang, Yunjian Hu, Wen Peng, Jie Sun

“…To address these issues, we propose YOLOLS, a lightweight and efficient detection model derived from YOLOv8n and optimized for real-time edge deployment. …”
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Spectral Efficiency Improved 2D-PAM8 Trellis Coded Modulation for Short Reach Optical System by Yan Fu, Meihua Bi, Da Feng, Xin Miao, Hao He, Weisheng Hu

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Efficiency of three dimension Au–MnO2 nanostructure as visible adsorption based detector of histamine sensing by Siti Febtria Asrini Sugito, Mochamad Zakki Fahmi, Miratul Khasanah, Septianti Putri Sophiar, Jia-yaw Chang, Gasidit Panomsuwan

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A novel sodium Iron silicate composite with chitosan for efficient removal of Cd(II) ions from water by Mohamed S. Kamel, Ehab A. Abdelrahman, Zinab M. Anwar, Samir M. El Rayes, Mortaga M. Abou-Krisha, Raed M. Hegazey, Hanan Alhussain

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π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing by Xiang Zhang, Tianze Ling, Zhi Jin, Sheng Xu, Zhiqiang Gao, Boyan Sun, Zijie Qiu, Jiaqi Wei, Nanqing Dong, Guangshuai Wang, Guibin Wang, Leyuan Li, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Fuchu He, Wanli Ouyang, Cheng Chang, Siqi Sun

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Method on Efficient Operation of Multiple Models for Vision-Based In-Flight Risky Behavior Recognition in UAM Safety and Security by Byeonghun Kim, Byeongjoon Noh, Kyowon Song

“…It can effectively perform roles such as detecting prohibited items and recognition of dangerous/abnormal behavior. …”
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A method for detecting abnormal electricity prices at charging stations based on two rounds of clustering by XUE Xiaohui, ZHANG Wen, ZHANG Jing, CHEN Yan, ZHOU Chun, CHEN Liang, CAO Zengwei

“…Due to the complexity of electricity pricing policies, multiple implementation steps, and difficulty in regulation, errors in electricity pricing implementation occur from time to time. …”
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Automatic Detection of Landslide Surface Cracks from UAV Images Using Improved U-Network by Hao Xu, Li Wang, Bao Shu, Qin Zhang, Xinrui Li

“…Surface cracks are key indicators of landslide deformation, crucial for early landslide identification and deformation pattern analysis. However, due to the complex terrain and landslide extent, manual surveys or traditional digital image processing often face challenges with efficiency, precision, and interference susceptibility in detecting these cracks. …”
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