Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

“…To address these issues, we introduce a novel one-stage network that enables real-time detection of insulator faults on mobile devices. We designed a new module that optimises the computational complexity of networks and fused the module with the attention mechanism SimAM to solve the problem of low efficiency in detecting flashover faults. …”
Get full text

An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

“… In recent years, Deep Neural Networks (DNN) have demonstrated remarkable success in various domains, including Intrusion Detection Systems (IDS). The ability of DNN to learn complex patterns from large datasets has significantly improved IDS performance, leading to more accurate and efficient threat detection. …”
Get full text

A Sparse Pooling Adversarial Learning Framework for Anomaly Event Detection by ZHANG, M., HU, H., LI, Z.

“…However, due to factors of complex background, large changes in scale, and the randomness of abnormal events, causing abnormal event detection poses significant challenges. …”
Get full text

An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

“… In recent years, Deep Neural Networks (DNN) have demonstrated remarkable success in various domains, including Intrusion Detection Systems (IDS). The ability of DNN to learn complex patterns from large datasets has significantly improved IDS performance, leading to more accurate and efficient threat detection. …”
Get full text

Multiscale Information Fusion Based on Large Model Inspired Bacterial Detection by Zongduo Liu, Yan Huang, Jian Wang, Genji Yuan, Junjie Pang

“…Accurate and efficient bacterial detection is essential for public health and medical diagnostics. …”
Get full text

High‐Sensitivity Dopamine Detection with Copper Terephthalate‐Modified Carbon Electrode by Aleksander Ejsmont, Klaudia Bucoń, Teresa Łuczak, Joanna Goscianska

“…This work positions Cu‐MOFs as scalable, efficient, and competitive alternatives to complex, multicomponent sensors for neurotransmitter detection.…”
Get full text

Spectral Clustering-Guided News Environments Perception for Fake News Detection by Kun Wang, Yuzhen Yang, Xiaoyang Wang

“…Then, we introduce a shared parameter multitask learning framework that treats different news environments as independent tasks and architects GRU bootstrapping modules with attention mechanisms to help aggregate features from different environments efficiently and interpretably. Finally, we provide textual perspective and stylistic perspective approaches during the detection process and soften the loss terms in multiple environments to alleviate the strict constraints, thus making it more compatible with the fake news detection task. …”
Get full text

Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…Road event detection is critical for tasks such as monitoring, anomaly detection, and optimization. …”
Get full text

Enhancing surface detection: A comprehensive analysis of various YOLO models by G. Deepti Raj, B. Prabadevi

“…Version 5 of You Only Look Once (YOLO), a precisely optimized learning model, has undergone extensive testing on steel strip datasets, providing effective solutions for recognition and detection in industry environments. This study presents an improved YOLOv5 detection model, exploiting the efficient channel attention (ECA) and coordinated attention (CoordAtt) mechanisms. …”
Get full text

Explainable Anomaly Detection Based on Operational Sequences in Industrial Control Systems by Ka-Kyung Kim, Joon-Seok Kim, Ieck-Chae Euom

“…Many anomaly detection algorithms based on deep learning models have good performance but often involve complex neural network structures, creating a black-box issue where users cannot interpret the decisions made by the models. …”
Get full text

SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…Specifically, the conventional multi-head self-attention (MHSA) mechanism is replaced with Efficient Additive Attention (EAA), which facilitates more efficient feature interaction while substantially reducing computational complexity. …”
Get full text

Fast and accurate obstacle detection based on stereo vision and deep learning by S. Badrloo, S. Badrloo

“…The ability to detect and avoid obstacles is essential for ensuring the safe and efficient navigation of mobile robots. …”
Get full text

CGTS: graph transformer-based anomaly detection in controller area networks by Xue Zhou, Guihe Qin, Yanhua Liang, Jiaru Song, Wanning Liu, Qingxin Liu

“…These results highlight CGTS can effectively detect multiple injection attacks and significantly improve the CAN bus intrusion detection performance.…”
Get full text

A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

“…Compared to other methods, our approach outperforms them in both performance and efficiency, fulfilling the real-time and precise defect detection needs of photodetectors.…”
Get full text

Multimodal-Based Non-Contact High Intraocular Pressure Detection Method by Zibo Lan, Ying Hu, Shuang Yang, Jiayun Ren, He Zhang

“…To address these limitations, we present a multi-modal framework incorporating CycleGAN for data augmentation, Swin Transformer for visual feature extraction, and the Kolmogorov–Arnold Network (KAN) for efficient fusion of heterogeneous data. KAN approximates complex nonlinear relationships with fewer parameters, making it effective in small-sample scenarios with intricate variable dependencies. …”
Get full text

Lightweight Detection of Train Underframe Bolts Based on SFCA-YOLOv8s by Zixiao Li, Jinjin Li, Chuanlong Zhang, Huajun Dong

“…To achieve efficient detection, a lightweight detection method based on SFCA-YOLOv8s is proposed. …”
Get full text

Copper Nodule Defect Detection in Industrial Processes Using Deep Learning by Zhicong Zhang, Xiaodong Huang, Dandan Wei, Qiqi Chang, Jinping Liu, Qingxiu Jing

“…The surface of cathodic copper plates is often affected by various electrolytic process factors, resulting in the formation of nodule defects that significantly impact surface quality and disrupt the downstream production process, making the prompt detection of these defects essential. At present, the detection of cathode copper plate nodules is performed by manual identification. …”
Get full text

Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8 by Tianxin Zhang, Fuwei Wang, Weimin Wang, Qihao Zhao, Weijun Ning, Haodong Wu

“…Fire has consistently posed a significant disaster risk worldwide. Current fire detection methods primarily rely on traditional physical sensors such as light, smoke, and temperature detectors, which often struggle in complex environments. …”
Get full text

Damage Detection of Steel Roof Systems Using Planet Optimization Algorithm by Thanh Sang-To, Van The Huy-Nguyen, Samir Khatir, The Vi-Huynh, Hoang Le-Minh, Thanh Cuong-Le

“…Also, the results proved that this technique provides an efficient solution to the complex problem with many constraints in unknown search space.…”
Get full text

Machine Learning-Based Network Anomaly Detection: Design, Implementation, and Evaluation by Pilar Schummer, Alberto del Rio, Javier Serrano, David Jimenez, Guillermo Sánchez, Álvaro Llorente

“…<b>Background:</b> In the last decade, numerous methods have been proposed to define and detect outliers, particularly in complex environments like networks, where anomalies significantly deviate from normal patterns. …”
Get full text