Driver Distraction Detection in Extreme Conditions Using Kolmogorov–Arnold Networks by János Hollósi, Gábor Kovács, Mykola Sysyn, Dmytro Kurhan, Szabolcs Fischer, Viktor Nagy

“…The results suggest that KANs can enhance driver distraction detection under challenging conditions, with improved resilience against adversarial attacks, particularly in low-complexity networks.…”
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Deep learning-assisted terahertz intelligent detection and identification of cancer tissue by Xingyu Wang, Yafei Xu, Rong Wang, Nuoman Tian, Zhengpeng Zhu, Shuting Fan, Liuyang Zhang, Ruqiang Yan, Xuefeng Chen

“…By combining the THz detection technique and artificial intelligence technique, here we propose a dense and efficient channel attention network (DECANet) framework-based THz diagnosis system for cancer prescreening. …”
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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. …”
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A Lightweight and Rapid Dragon Fruit Detection Method for Harvesting Robots by Fei Yuan, Jinpeng Wang, Wenqin Ding, Song Mei, Chenzhe Fang, Sunan Chen, Hongping Zhou

“…To enhance detection accuracy and satisfy the deployment constraints of edge devices, we propose YOLOv10n-CGD, a lightweight and efficient dragon fruit detection method designed for robotic harvesting applications. …”
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Weed detection in cornfields based on improved lightweight neural network model by Haicheng Wan, Shanping Wang

“…Based on the original YOLOv4, an improved lightweight weed detection model, YOLOv4-weeds, is proposed. By changing the main YOLOv4 feature extraction network into MobileNetV3-Small, combined with the depthwise separable convolution and inverse residual structure, and introducing a lightweight attention mechanism, this model reduces the image processing memory size and improves detection efficiency. …”
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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. …”
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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…It has been specifically designed to efficiently process and analyze vast and complex datasets commonly encountered in the financial sector, showcasing adaptability to the dynamic nature of big data environments. …”
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LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

“…A novel SEAM attention module is proposed to refine the features that represent both the spatial and channel information by leveraging the features from the Simple Attention Module (SimAM) and Efficient Channel Attention (ECA) mechanism. The HSM-EIoU loss function is also proposed to accurately detect a small traffic light by amplifying the loss for hard-sample objects. …”
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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.…”
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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.…”
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Artificial Intelligence in Wind Turbine Fault Detection and Diagnosis: Advances and Perspectives by Nejad Alagha, Anis Salwa Mohd Khairuddin, Zineddine N. Haitaamar, Obada Al-Khatib, Jeevan Kanesan

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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. …”
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A New Local Optimal Spline Wavelet for Image Edge Detection by Dujuan Zhou, Zizhao Yuan, Zhanchuan Cai, Defu Zhu, Xiaojing Shen

“…We propose a new LOSW-based edge detection algorithm (LOSW-ED), which introduces a structural uncertainty–aware modulus maxima (SUAMM) to detect highly uncertain edge samples, ensuring robustness in complex and noisy environments. …”
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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. …”
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Fragmented QRS complex in patients with systemic lupus erythematosus at the time of diagnosis and its relationship with disease activity. by Masahiro Hosonuma, Nobuyuki Yajima, Ryo Takahashi, Ryo Yanai, Taka-Aki Matsuyama, Eiji Toyosaki, Jumpei Saito, Kengo Kusano, Hiroshi Morita

“…Fragmented QRS (fQRS) complexes, defined by additional spikes in the QRS complex, are useful for identifying myocardial scars on electrocardiography and can be an independent predictor of cardiac events. …”
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Hyperspectral Simultaneous Anomaly Detection and Denoising: Insights From Integrative Perspective by Minghua Wang, Lianru Gao, Longfei Ren, Xian Sun, Jocelyn Chanussot

“…However, scholars have been addicted to developing numerous complex methods for separable two-stage denoising and anomaly detection (AD) tasks over the past years, rarely paying attention to the real effect of noises for subsequent intelligent interpretation. …”
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Detecting faults in electronic combustion engine control systems by acoustic parameters by V. D. Gabidulin, V. N. Dobromirov

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Image-based maturity detection for selective cauliflower harvesting in field condition by Ajay Kushwah, P.K. Sharma, H.L. Kushwaha, Brij Bihari Sharma, Naseeb Singh, Ramineni Harsha Nag, Manojit Chowdhury, Nrusingh Charan Pradhan, Gopal Carpenter, Silpa Mandal, Ali Salem

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Effect of age on complexity and causality of the cardiovascular control: comparison between model-based and model-free approaches. by Alberto Porta, Luca Faes, Vlasta Bari, Andrea Marchi, Tito Bassani, Giandomenico Nollo, Natália Maria Perseguini, Juliana Milan, Vinícius Minatel, Audrey Borghi-Silva, Anielle C M Takahashi, Aparecida M Catai

“…We found that: 1) MF approaches are more efficient than the MB method when nonlinear components are present, while the reverse situation holds in presence of high dimensional embedding spaces; 2) the CE method is the least powerful in detecting age-related trends; 3) the association of HP complexity on age suggests an impairment of cardiac regulation and response to STAND; 4) the relation of SAP complexity on age indicates a gradual increase of sympathetic activity and a reduced responsiveness of vasomotor control to STAND; 5) the association from SAP to HP on age during STAND reveals a progressive inefficiency of baroreflex; 6) the reduced connection from HP to SAP with age might be linked to the progressive exploitation of Frank-Starling mechanism at REST and to the progressive increase of peripheral resistances during STAND; 7) at REST the diminished association from RESP to HP with age suggests a vagal withdrawal and a gradual uncoupling between respiratory activity and heart; 8) the weakened connection from RESP to SAP with age might be related to the progressive increase of left ventricular thickness and vascular stiffness and to the gradual decrease of respiratory sinus arrhythmia.…”
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DRCO: Dense-Label Refinement and Cross Optimization for Semi-Supervised Object Detection by Yunlong Qin, Yanjun Li, Feifan Ji, Yan Liu, Yu Wang, Ji Xiang

“…In semi-supervised object detection (SSOD), the methods based on dense pseudo-labeling bypass complex post-processing while maintaining competitive performance compared to the methods based on sparse pseudo-labeling. …”
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