The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…But in practice, it is difficult to achieve both optimal detection accuracy and computational efficiency simultaneously due to limited computing resources. …”
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Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations. by Sarah M Zala, Doris Reitschmidt, Anton Noll, Peter Balazs, Dustin J Penn

“…Manually processing complex vocalization data is time-consuming and potentially subjective, and therefore, we developed an algorithm that automatically detects mouse ultrasonic vocalizations (Automatic Mouse Ultrasound Detector or A-MUD). …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…Proper thermal management ensures uniform heat distribution, which is essential for optimizing efficiency, safety, and reliability. However, obtaining comprehensive real-time temperature data for large-scale battery systems is challenging due to the high costs, complexity, and impracticality of deploying extensive sensor networks. …”
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A crosslinked eutectogel for ultrasensitive pressure and temperature monitoring from nostril airflow by Tao Liu, Qinan Wu, Huansheng Liu, Xiyang Zhao, Xin Yi, Jing Liu, Zhenzhen Nong, Bingpu Zhou, Qingwen Wang, Zhenzhen Liu

“…However, the developed methods only rely on single stimulus sensing for nostril airflow, which is extremely susceptible to interference in the complex environment, and severely affects the accuracy of detection results. …”
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An Algorithm for the Shape-Based Distance of Microseismic Time Series Waveforms and Its Application in Clustering Mining Events by Hao Luo, Ziyu Liu, Song Ge, Linlin Ding, Li Zhang

“…To improve the efficiency and accuracy of microseismic event extraction from time-series data and enhance the detection of anomalous events, this paper proposes a Multi-scale Fusion Convolution and Dilated Convolution Autoencoder (MDCAE) combined with a Constraint Shape-Based Distance algorithm incorporating volatility (CSBD-Vol). …”
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Targeted immunotherapy approaches for intraductal papillary neoplasm of the bile duct by Bahareh Sadri, Massoud Vosough

“…Abstract: Intraductal papillary neoplasm of the bile duct (IPNB) is a complex biliary tractneoplasm. Its classifications based on distinct clinical, pathological, andradiological features and gene mutations, are of paramount importance. …”
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Compact classification using the biomimetic properties of ultrafast spiking microlaser neurons by Gibaek Kim, Matthieu Dubernard, Sami V El-Nakouzi, Amir-Hossein Masominia, Sylvain Barbay, Laurie E Calvet

“…This enables the training of a compact, energy efficient spiking photonic architecture that takes advantage of biomimetic properties to detect important features of the data. …”
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Research on Buckwheat Weed Recognition in Multispectral UAV Images Based on MSU-Net by Jinlong Wu, Xin Wu, Ronghui Miao

“…Targeting low detection efficiency in complex agricultural environments and inability of multispectral input in weed recognition of minor grain based on unmanned aerial vehicles (UAVs), a semantic segmentation model for buckwheat weeds based on MSU-Net (multispectral U-shaped network) was proposed to explore the influence of different band optimizations on recognition accuracy. …”
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BIOTHREAT EARLY ASSIST AND RESPONSE COMMAND SYSTEM (BEAR-CS) by Rexhep Mustafovski, Aleksandar Risteski, Tomislav Shuminoski

“…The integration of this system into military operations ensures not only quicker reaction times but also increased efficiency during mission planning and execution. …”
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Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

“…Modern radar systems face increasingly complex challenges in tasks such as detection, tracking, and identification. …”
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A Novel Approach to Multi-Class Crack Classification: ResNet50 Enhanced with Squeeze-and-Excitation Blocks by Mazleenda Mazni, Abdul Rashid Husain, Devi Willieam Anggara, Mohd Ibrahim Shapiai, Riyadh Zulkifli, Munirah Onn

“…Unlike conventional models, which lack feature recalibration capabilities, the embedded SE block adaptively enhances channel-wise feature importance, significantly improving crack detection performance under complex conditions such as lighting variations and background noise. …”
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A Frequency-Aware Transformer for Multiscale Fault Diagnosis in Electrical Machines by Yurim Choi, Inwhee Joe

“…However, conventional fault diagnosis methods struggle to effectively capture complex time-frequency patterns, limiting their ability to perform early fault detection and accurate classification. …”
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A Multivariable Probability Density-Based Auto-Reconstruction Bi-LSTM Soft Sensor for Predicting Effluent BOD in Wastewater Treatment Plants by Wenting Li, Yonggang Li, Dong Li, Jiayi Zhou

“…The precise detection of effluent biological oxygen demand (BOD) is crucial for the stable operation of wastewater treatment plants (WWTPs). …”
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Research on recognition of diabetic retinopathy hemorrhage lesions based on fine tuning of segment anything model by Sujuan Tang, Qingwen Wu

“…Abstract Diabetic Retinopathy (DR) demands precise hemorrhage detection for early diagnosis, yet manual identification faces challenges due to hemorrhagic lesions’ varied sizes, complex shapes, and color similarities to surrounding tissues, which obscure boundaries and reduce contrast. …”
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Research Progress and Applications of Artificial Intelligence in Agricultural Equipment by Yong Zhu, Shida Zhang, Shengnan Tang, Qiang Gao

“…The key innovations are highlighted in areas such as object detection and recognition (e.g., a K-nearest neighbor (KNN) achieved 98% accuracy in distinguishing vibration signals across operation stages); autonomous navigation and path planning (e.g., a deep reinforcement learning (DRL)-optimized task planner for multi-arm harvesting robots reduced execution time by 10.7%); state perception (e.g., a multilayer perceptron (MLP) yielded 96.9% accuracy in plug seedling health classification); and precision control (e.g., an intelligent multi-module coordinated control system achieved a transplanting efficiency of 5000 plants/h). …”
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CAEB7-UNet: An Attention-Based Deep Learning Framework for Automated Segmentation of C-Spine Vertebrae in CT Images by Abhishek Kumar Pandey, Kedarnath Senapati, G. P. Pateel

“…This study presents a novel channel attention-based EfficientNetB7-UNet (CAEB7-UNet) method to address this complex task effectively. …”
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Unbiased analysis of obesity related, fat depot specific changes of adipocyte volumes and numbers using light sheet fluorescence microscopy. by Natalie Theobalt, Isabel Hofmann, Sonja Fiedler, Simone Renner, Georg Dhom, Annette Feuchtinger, Axel Walch, Martin Hrabĕ de Angelis, Eckhard Wolf, Rüdiger Wanke, Andreas Blutke

“…LSFM allows for accurate and efficient determination of relevant quantitative morphological adipocyte parameters. …”
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Biologically inspired hybrid model for Alzheimer’s disease classification using structural MRI in the ADNI dataset by Houmem Slimi, Imen Cherif, Sabeur Abid, Mounir Sayadi

“…The SNN introduces architectural sparsity via spike-based computation, reducing overfitting and enhancing generalization while aligning with neuromorphic principles for energy-efficient deployment. By bridging deep learning with neuromorphic principles, this work advances AD diagnostic frameworks, offering a computationally efficient and biologically plausible approach for clinical neuroimaging. …”
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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…In recent years, the detection and analysis of near-fault pulse-like ground motions have become increasingly crucial due to their potential to cause significant structural damage during seismic events. …”
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IoT-Enhanced Smart Parking Management With IncepDenseMobileNet for Improved Classification by Xiaoxia Zheng, Wenxi Feng, Ning Wang, Huhemandula

“…The IncepDenseMobileNet (IDMN) model integrates Inception, DenseNet, and MobileNet architectures to proficiently capture complex patterns via multi-scale feature extraction and efficient depthwise separable convolutions. …”
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