Explainable correlation-based anomaly detection for Industrial Control Systems by Ermiyas Birihanu, Imre Lendák

“…Anomaly detection is vital for enhancing the safety of Industrial Control Systems (ICS). …”
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Theoretical approaches to detecting anomalies in meter readings in scientific literature by D.V. Furikhata, T.A. Vakalyuk

“…Classification methods of supervised learning are analysed, which require pre-labelled data for model training but provide high accuracy in detecting known types of anomalies. The prospects for further development of anomaly detection technologies in the context of integrating IoT devices, technology development and implementing more complex deep learning algorithms are considered.…”
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Kneeliverse: A universal knee-detection library for performance curves by Mário Antunes, Tyler Estro, Pranav Bhandari, Anshul Gandhi, Geoff Kuenning, Yifei Liu, Carl Waldspurger, Avani Wildani, Erez Zadok

“…Additionally, Kneeliverse extends these algorithms to detect multiple knees and elbows in complex curves, employing a recursive approach. …”
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Daxx and HIRA go viral – How chromatin remodeling complexes affect DNA virus infection by Julia Mai, Masih Nazari, Thomas Stamminger, Sabrina Schreiner

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Mechanochromic Suction Cups for Local Stress Detection in Soft Robotics by Goffredo Giordano, Rob Bernardus Nicolaas Scharff, Marco Carlotti, Mariacristina Gagliardi, Carlo Filippeschi, Alessio Mondini, Antonio Papangelo, Barbara Mazzolai

“…Advancements in smart soft materials are enhancing the capabilities of robotic manipulators in object interactions and complex tasks. Mechanochromic materials, acting as lightweight sensors, offer easily interpretable visual feedback for localized stress detection, structural health monitoring, and energy‐efficient robotic skins. …”
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Study on PV Defect Detection Based on CWE YOLOv8 by Xiaojuan Zhang, Ruixu Yao, Bo Jing, Xiaoxuan Jiao, Mengdi Ren

“…The traditional upsampling process is replaced by the WaveletPool module, which uses wavelet transforms to enhance multi-scale features and improve feature resolution. A lightweight EfficientHead detection head is also introduced to boost the model’s accuracy and robustness in complex detection scenarios. …”
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Model-Based Detection of Coordinated Attacks (DCA) in Distribution Systems by Nitasha Sahani, Chen-Ching Liu

“…Existing research in intrusion detection is primarily focused on the transmission network and limited to detecting individual attacks. …”
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CNN and Transfer Learning methods for enhanced dermatological disease detection by Habibulla C. Venkataiah, T. Jayachandra Prasad, G. Gopinath, B. Charitha, G. Dharma Teja, B. Lomith Reddy

“…This final model has been a pragmatic and accessible tool for early detection and diagnosis of skin disease. The feature here is an attempt to provide a more accurate, efficient, and user-friendly diagnostic solution through the incorporation of advanced methods of Transfer Learnin3g and visualization.…”
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Detection of hydrophobicity grade of insulators based on AHC-YOLO algorithm by Shaotong Pei, Weiqi Wang, Peng Wu, Chenlong Hu, Haichao Sun, Keyu Li, Mianxiao Wu, Bo Lan

“…Moreover, considering the real-time requirements for insulator hydrophobicity detection in practical operations, the model must be lightweight to speed up the detection process. …”
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Remote Sensing Change Detection by Pyramid Sequential Processing With Mamba by Jiancong Ma, Bo Li, Hanxi Li, Siying Meng, Ruitao Lu, Shaohui Mei

“…Change detection (CD) in remote sensing imagery is crucial for monitoring environmental variations over time. …”
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Smart deep learning model for enhanced IoT intrusion detection by Faisal S. Alsubaei

“…This paper addresses these limitations with large preprocessing steps followed by hyperparameter tuning of machine learning XGBoost and deep learning Sequential Neural Network (OSNN) algorithms through Grid Search for their best values to improve multiclass intrusion detection across varied datasets. These deep models were then augmented with a variety of various filters, kernels, activation functions, and regularization techniques in an attempt to boost them in detecting complex, multiclass intrusion patterns. …”
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Exploration of machine learning approaches for automated crop disease detection by Annu Singla, Ashima Nehra, Kamaldeep Joshi, Ajit Kumar, Narendra Tuteja, Rajeev K. Varshney, Sarvajeet Singh Gill, Ritu Gill

“…Recent advancements in machine learning (ML) offer promising alternatives by automating the disease detection processes with high precision and efficiency. …”
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Improved RRT-Based Obstacle-Avoidance Path Planning for Dual-Arm Robots in Complex Environments by Jing Wang, Genliang Xiong, Bowen Dang, Jianli Chen, Jixian Zhang, Hui Xie

“…To address the obstacle-avoidance path-planning requirements of dual-arm robots operating in complex environments, such as chemical laboratories and biomedical workstations, this paper proposes ODSN-RRT (optimization-direction-step-node RRT), an efficient planner based on rapidly-exploring random trees (RRT). …”
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Network-based intrusion detection using deep learning technique by Muhammad Farhan, Hafiz Waheed ud din, Saadat Ullah, Muhammad Sajjad Hussain, Muhammad Amir Khan, Tehseen Mazhar, Umar Farooq Khattak, Ines Hilali Jaghdam

“…Abstract A high growth rate in network traffic and the complexity of cyber threats have made it necessary to create more effective and flexible intrusion detection systems. …”
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HCRP-YOLO: A lightweight algorithm for potato defect detection by Haojie Liao, Guanping Wang, Siyu Jin, Yan Liu, Wei Sun, Sen Yang, Lu Wang

“…In response, this study proposes HCRP-YOLO system, which is based on the YOLOv8n architecture and aims to further enhance lightweight, precision, and efficiency. The method first introduces the lightweight HGNetv2 backbone network and incorporates a channel scaling feature to reduce model complexity, while dynamically adjusting the number of feature channels, thereby improving detection performance. …”
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DVCW-YOLO for Printed Circuit Board Surface Defect Detection by Pei Shi, Yuyang Zhang, Yunqin Cao, Jiadong Sun, Deji Chen, Liang Kuang

“…The accurate and efficient detection of printed circuit board (PCB) surface defects is crucial to the electronic information manufacturing industry. …”
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YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

“…The experimental results and comparative analysis with similar network models indicate that the YOLO-MECD model has achieved significant improvements in both detection performance and computational efficiency. …”
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A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

“…The underground environment of coal mines is complex and has more safety hazards. Personnel detection is an important part of ensuring safe production in coal mines and building smart mines. …”
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Spatial Identification and Distribution Pattern of the Complexity of Rural Poverty in China Using Multisource Spatial Data by Zhenyu Qi, Jinghu Pan, Yaya Feng

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Optimizing Monkeypox Lesions Detection With a Lightweight Hybrid Model by Mehdhar S. A. M. Al-Gaashani, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Abduljabbar S. Ba Mahel, Ahmed Aziz, Mashael M. Khayyat, Ammar Muthanna

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