Adaptive malware identification via integrated SimCLR and GRU networks by Faisal S. Alsubaei, Abdulwahab Ali Almazroi, Walid Said Atwa, Abdulaleem Ali Almazroi, Nasir Ayub, N. Z. Jhanjhi

“…SimCLR-GRU provides a scalable and decisive answer to modern cyberspace’s changing malware detection problem.…”
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Underground personnel recognition based on low-light enhancement of infrared and visible light image fusion by NAN Jingjing, PAN Hongguang, JIANG Ze, ZHANG Libin, ZHANG Huipeng

“…Compared to the infrared modality, accuracy increased by an average of 2.1%, recall rate increased by 5.1%, and mAP@0.5 increased by 4.1%. Meanwhile, the detection speed reached 31.2 frames/s, solving problems such as misdetection and missed detection caused by unclear personnel features in low-light underground scenarios.…”
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PlutoNet: An efficient polyp segmentation network with modified partial decoder and decoder consistency training by Tugberk Erol, Duygu Sarikaya

“…Abstract Deep learning models are used to minimize the number of polyps that goes unnoticed by the experts and to accurately segment the detected polyps during interventions. Although state‐of‐the‐art models are proposed, it remains a challenge to define representations that are able to generalize well and that mediate between capturing low‐level features and higher‐level semantic details without being redundant. …”
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All-Optical Demodulation Fiber Acoustic Sensor With Real-Time Controllable Sensitivity Based on Optical Vernier Effect by Shuai Wang, Shun Wang, Rui-Bo Jin, Mingzhe Feng, Shun Wu, Liang Zhang, Peixiang Lu

“…This letter presents a fiber acoustic sensor with real-time controllable sensitivity based on the optical vernier effect, which is possibly a solution to such a problem. The optical vernier structure with amplified and real-time tunable detection sensitivity is formed by cascading a Sagnac interferometer and a laboratory-made tunable Fabry–Perot interferometer (FPI). …”
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Automated approach for fetal and maternal health management using light gradient boosting model with SHAP explainable AI by Nisreen Innab, Shtwai Alsubai, Ebtisam Abdullah Alabdulqader, Aisha Ahmed Alarfaj, Muhammad Umer, Silvia Trelova, Imran Ashraf

“…The proposed methodology makes use of data upsampled using the synthetic minority oversampling technique (SMOTE) to handle the class imbalance problem that is very crucial in medical diagnosing with a light gradient boosting machine. …”
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Review of dengue, zika and chikungunya infections in nervous system in endemic areas by Marzia Puccioni-Sohler, Cristiane Nascimento Soares, Paulo Pereira Christo, Sérgio Monteiro de Almeida

“…The emergence and re-emergence of viral infections transmitted by mosquitoes constitute a serious human public health problem. The neurological manifestations caused by these viruses have a high potential for death or sequelae. …”
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Improved YOLOv8 Algorithm was Used to Segment Cucumber Seedlings Under Complex Artificial Light Conditions by Duokuo Zhang, Na Li, Mingfu Zhao, Kun Xu

“…Aiming at the challenging problem of cucumber seedling leaf segmentation under a complex artificial lighting environment, this study proposes an improved complex lighting YOLOv8 (CL-YOLOv8) model based on YOLOv8. …”
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Lexical Emergence on Reddit: An Analysis of Lexical Change on the “Front Page of the Internet” by Hanna Mahler

“…Secondly, words being attested in a representative corpus was proposed as a more realistic criterion for classifying a word as ‘established’ compared to its inclusion in standard dictionaries. A third problem is that the methodology only allows for the detection of single-word units, which is not an accurate representation of the changes taking place, as several of the emerging lexemes appear to be part of compounds.…”
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Viral gastroenteritis in children: modern concepts of epidemiology and prevention by K. D. Ermolenko, Yu. V. Lobzin, N. V. Gonchar

“…More than 60 original articles and reviews were analyzed in order to study the current state of the epidemiology and prevention of acute intestinal infections (AII) of viral etiology in the world. Interest in a problem of viral AII is determined by their widest prevalence and huge costs associated with the elimination of their consequences. …”
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Deep learning–assisted real-time container corner casting recognition by Jaecheul Lee

“…Existing techniques use various traditional laser-based and vision-based methods for corner casting detection. Challenging weather conditions, varying lighting conditions, light reflections from ground, and container rusting conditions are the main problems that affect the performance of automated cranes. …”
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多尺度主元坐标变换在轴承故障声发射信号增强检测中的应用 by 张晓涛, 唐力伟, 王平, 邓士杰

“…Aiming at the problem of weak feature extraction and recognition in the bearing acoustic emission signal processing,multi-scale principal component coordinate transformation is proposed to enhance fault feature.Firstly,the signal is decomposed by wavelet package,and the sub-band reconstruction component is converted to a new linear space by principal component analysis,and the signal fault feature is enhanced.Finally,the method performance is verified by simulation signal and testing signal,the results show that multi-scale principal component coordinate transformation has obvious enhancement effect in bearing fault detection.…”
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Port terminal mobile recognition based on combined YOLOv5s-DeepSort. by Chengzhi Wang, Donghong Chen, Zhen Liu, Yuanhao Li, Yifei Wang, Sanglan Zhao

“…To solve the problem of reduced positioning accuracy caused by changes in scale, background and occlusion in port and dock video images, this research proposes an enhanced model combining YOLOv5s-DeepSORT, integrating target load recognition and trajectory tracking to improve adaptability to dock environments. …”
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Real-time Diagnosis and Prediction of Grounding Insulation Fault inTrain Power Supply System by QIN Fangfang, ZHENG Caihui, LI Xueming, LI Peng

“…In order to solve the problem of fault location and real-time evaluation of fault development trend, it proposed a real-time diagnosis and prediction method based on signal feature pattern recognition. …”
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Lightweight Sheep Face Recognition Model Combining Grouped Convolution and Parameter Fusion by Gaochao Liu, Lijun Kang, Yongqiang Dai

“…When these models are deployed on mobile or embedded devices, problems such as reduced model recognition accuracy and increased recognition time arise. …”
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Efficient Brain Tumor Segmentation for MRI Images Using YOLO-BT by Mengying Xiong, Aiping Wu, Yue Yang, Qingqing Fu

“…Aiming at the problems of inaccurate segmentation and low detection efficiency caused by irregular tumor shape and large size differences in brain MRI images, this study proposes a brain tumor segmentation algorithm, YOLO-BT, based on YOLOv11. …”
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An interactive ball training partner robot based on YOLOv5 by Zeng Yangji, Liu Zihong, Cai Yong, Guo Xingchen, Mo Jinlong

“…Compared with other algorithms based on feature matching and small target detection using gestures, the robot has higher detection speed and accuracy, which makes the robot more intelligent.…”
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AI-driven thermography-based fault diagnosis in single-phase induction motor by Muhammad Atif, Shoaib Azmat, Faisal Khan, Fahad R. Albogamy, Adam Khan

“…Many fault diagnosis methods have been proposed to detect bearing faults based on contact sensors, but they have accessibility problems. …”
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Bearing Early Fault Diagnosis Based on an Improved Multiscale Permutation Entropy and SVM by Qunyan Jiang, Juying Dai, Faming Shao, Shengli Song, Fanjie Meng

“…In order to solve the problem that only considering a single coarse-grained sequence under a certain scale may lead to the loss of feature information, this paper proposed to calculate the time series with equal overlapping segments, that was to consider all coarse-grained sequences under the same scale to reflect the feature information of fault signals more comprehensively. …”
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Research on Calibration Algorithm of Camera and LiDAR for Transport Vehicles in Open-pit Mines by XU Yanghan, LIN Jun, KANG Gaoqiang, YOU Jun, YUE Wei, TONG Hao

“…In the intelligent driving system of transport vehicles in open-pit mines, the data fusion of camera and LiDAR plays a vital role in the detection, recognition and tracking of obstacles. Aiming at the problem of camera and LiDAR spatial coordinate unity, that is establishing the correspondence between 2D coordinate system of image and 3D coordinate system of point cloud, this paper proposes a camera and LiDAR calibration method based on chessboard calibration board. …”
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ImageNomer: Description of a functional connectivity and omics analysis tool and case study identifying a race confound by Anton Orlichenko, Grant Daly, Ziyu Zhou, Anqi Liu, Hui Shen, Hong-Wen Deng, Yu-Ping Wang

“…This exacerbates two problems found in these types of data: demographic confounds and quality control in the face of high dimensionality of features. …”
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