Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data by Md Ariful Islam Mozumder, Tagne Poupi Theodore Armand, Rashadul Islam Sumon, Shah Muhammad Imtiyaj Uddin, Hee-Cheol Kim

“…Our study culminates in the development of an automated system for robust pet (cat) activity analysis using artificial intelligence techniques, featuring a 1D-CNN-based approach. …”
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Classification and Detection of Rumors Related to COVID-19 Using Machine Learning-Based Smart Techniques by Yancheng Yang, Junqiao Zhai, Shah Nazir

“…After studying different information detection techniques, various features have been identified from the literature. …”
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Protein networks reveal detection bias and species consistency when analysed by information-theoretic methods. by Luis P Fernandes, Alessia Annibale, Jens Kleinjung, Anthony C C Coolen, Franca Fraternali

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PS-GCN: psycholinguistic graph and sentiment semantic fused graph convolutional networks for personality detection by Wenjuan Liu, Zhengyan Sun, Subo Wei, Shunxiang Zhang, Guangli Zhu, Lei Chen

“…P-GCN is designed to capture the dependency information between psycholinguistic features, while S-GCN utilises syntactic structure analysis to gather more abundant information features and enhance semantic understanding ability. …”
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Detection of Ship Wakes in Dynamic Sea Surface Video Sequences: A Data-Driven Approach by Chengcheng Yu, Yanmei Zhang, Meifang Xiao, Zhibo Zhang

“…In order to enhance the detection of maritime vessel targets, considering the causal relationship between the motion of vessels and their wakes, as well as the characteristics of ship wakes such as large diffusion range and distinctive features, this paper proposes a data-driven method based on Dynamic Mode Decomposition (DMD) for detecting and analyzing ship wakes in sea surface videos. …”
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AI may help to predict thyroid nodule malignancy based on radiomics features from [18F]FDG PET/CT by Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek

“…Conclusions With an AI-based algorithm using radiomics features it is possible to detect the malignancy of thyroid nodule. …”
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A fuzzy system for detection of road slipperiness in Arctic snowy conditions using LiDAR by Aqsa Rahim, Sushmit Dhar, Fuqing Yuan, Javad Barabady

“…The analysis establishes a strong correlation between LiDAR intensity and the coefficient of friction, enabling reliable detection of surface conditions. …”
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Enhancing smart contract security: Leveraging pre‐trained language models for advanced vulnerability detection by Fei He, Fei Li, Peili Liang

“…Traditional methods for detecting these vulnerabilities, including manual inspections and automated static analysis, are plagued by issues such as high rates of false positives and overlooked security flaws. …”
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On the Nuances of Multimodal Laughter Detection: Where, Why, and When Visual Insight Augments Audio in Classification by Liviu-Alexandru Marina, Corina Dimitriu

“…This paper explores the impact of visual input on traditional audio classification, focusing on the analysis of audiovisual data compilation and the interaction between modalities in laughter detection. …”
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Evaluation of polarization modes and spatial resolution of PALSAR-2 for canal detection accuracy in Indonesia peatlands by Muhammad Haidar, Wataru Takeuchi

“…In contrast, the 25-meter resolution showed significant limitations in detecting fine-scale canal features. These findings highlight the importance of polarization selection and model design for accurate canal segmentation, while also revealing resolution–accuracy trade-offs relevant to peatland management efforts.…”
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Automated detection of Parkinson’s disease using improved linknet-ghostnet model based on handwriting images by P Pradeep, J Kamalakannan

“…Then, modified PHOG, Deep features and Shape features are extracted. Finally, detection is performed using hybrid Improved LinkNet and Ghostnet models, termed (ILN-GNet), whose outcomes indicate if the individual is healthy or affected. …”
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Domain Generalized Open-Set Fault Detection and Diagnosis for Belt Conveyor Systems With Prototype Learning by Jinyou Kim, Ilkyu Yi, Young-Joo Suh

“…Various approaches have been explored for fault detection and diagnosis (FDD) in belt conveyor systems, but research specifically addressing the unique features of these systems and providing a comprehensive analysis remains limited. …”
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A General Purpose Adaptive Fault Detection and Diagnosis Scheme for Information Systems with Superheterodyne Receivers by Dengwei Song, Hongmei Liu, Le Qi, Bo Zhou

“…A general purpose fault detection and diagnosis scheme based on observers and residual error analysis was proposed in this study. …”
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YOLO11m-SCFPose: An Improved Detection Framework for Keypoint Extraction in Cucumber Fruit Phenotyping by Huijiao Yu, Xuehui Zhang, Jun Yan, Xianyong Meng

“…Additionally, an improved C3K2_PartialConv neck module is used to enhance information interaction and fusion among multi-scale features while maintaining computational efficiency. …”
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Automated Soma Detection in Whole-Brain Imaging via Post-Tracing Multi-Furcation Morphometry by Gu Xiaoqin

“…In this study, we propose a novel, automated pipeline that leverages local morphometry features, particularly multi-furcation clusters, to detect soma after initial fiber tracing in high- resolution, large-scale whole mouse brain images. …”
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Objective Detection of Newborn Infant Acute Procedural Pain Using EEG and Machine Learning Algorithms by Jean‐Michel Roué, Amir Avnit, Behnood Gholami, Wassim M. Haddad, Kanwaljeet J. S. Anand

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Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology by Andrew Broad, Alexander Wright, Clare McGenity, Darren Treanor, Marc de Kamps

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Enhancing Fall Detection Accuracy: The Ground-Face Coordinate System for 3D Accelerometer Data by Abdullah Talha Sözer

“…To assess the potential of the vertical component of ground-face referenced accelerometer signals for FD, it was compared with the commonly used acceleration magnitude signal. Detailed analysis was conducted using frequently preferred features in FD studies, and fall detection was performed with various classifiers. …”
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Research on wind turbine blade fault detection based on DenseNet-TL combined with ELM by Dianming WANG, Xue PAN, Jian MA, Yuzhang DAI, Chengjun SUN, Shibin LI, Xiaoju YIN

“…The image samples are collected as training set, and the image features are effectively extracted using the improved DenseNet, which is combined with Extreme Learning Machines to improve the classification accuracy of the detection. 8000 images were collected, and the analysis results for the test set of images show that the detection accuracy of this model is higher than that of the DenseNet, ResNet and AlexNet models of migration learning, reaching more than 99%, and obtaining a more accurate preventive detection of wind turbine blade faults.…”
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Enhanced Vision-Based Quality Inspection: A Multiview Artificial Intelligence Framework for Defect Detection by Geethika Bhavanasi, Davy Neven, Manuel Arteaga, Sina Ditzel, Sam Dehaeck, Abdellatif Bey-Temsamani

“…We propose MV-UNet, a novel early fusion architecture that aligns and aggregates multiview features using a transformation block to enhance detection accuracy. …”
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