Application of YOLO11 Model with Spatial Pyramid Dilation Convolution (SPD-Conv) and Effective Squeeze-Excitation (EffectiveSE) Fusion in Rail Track Defect Detection by Weigang Zhu, Xingjiang Han, Kehua Zhang, Siyi Lin, Jian Jin

“…With the development of the railway industry and the progression of deep learning technology, object detection algorithms have been gradually applied to track defect detection. …”
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Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules by Zhi Li, Wenjing Zhang, Jinyi Huang, Ling Lu, Dongming Xie, Jinrong Zhang, Jiamin Liang, Yuepeng Sui, Linyuan Liu, Jianjun Zou, Ao Lin, Lei Yang, Fuman Qiu, Zhaoting Hu, Mei Wu, Yibin Deng, Xin Zhang, Jiachun Lu

“…Currently, more than 90% of PNs detected by screening tests are benign, with a false positive rate of up to 96.4%. …”
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AILDP: a research on ship number recognition technology for complex scenarios by Tianjiao Wei, Zhuhua Hu, Yaochi Zhao, Xiyu Fan

“…Firstly, in the detection phase, for the problem of varying size and position in the ship number recognition task, the detection effect is optimized by a module (AIFI_LPE) that combines feature interaction and learned position encoding. …”
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A stacked ensemble model for traffic conflict prediction using emerging sensor data by Bowen Cai, Léah Camarcat, Nicolette Formosa, Mohammed Quddus

“…This model integrates a Random Forest (RF), three-layer Deep Neural Networks (DNN), Support Vector Machine Radial (SVM-R), and a Gradient Boosting Model (GBM) meta layer to enhance prediction accuracy. The Recursive Feature Elimination (RFE) algorithm is then employed to identify the most influential SSMs for conflict prediction in each scenario. …”
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Online monitoring data processing methods for railway slopes and its application: A case study of the Shuohuang Railway by Mu GU

“…Initially, the 3σ criterion is employed for outlier detection in monitoring data, which is then corrected using the Kalman filter algorithm. …”
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Research on unsupervised domain adaptive bearing fault diagnosis method by WU ShengKai, SHAO Xing, WANG CuiXiang, GAO Jun

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Evaluating sowing uniformity in hybrid rice using image processing and the OEW-YOLOv8n network by Zehua Li, Zehua Li, Yihui Pan, Xu Ma, Yongjun Lin, Xicheng Wang, Hongwei Li

“…Compared to the advanced object detection algorithms such as Faster-RCNN, SSD, YOLOv4, YOLOv5s YOLOv7-tiny, and YOLOv10s, the mAP of the new network increased by 5.2%, 7.8%, 4.9%, 2.8% 2.9%, and 3.3%, respectively. …”
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Zonal Estimation of the Earliest Winter Wheat Identification Time in Shandong Province Considering Phenological and Environmental Factors by Jiaqi Chen, Xin Du, Chen Wang, Cheng Cai, Guanru Fang, Ziming Wang, Mengyu Liu, Huanxue Zhang

“…Time-series datasets derived from Sentinel-1/2 imagery (2021–2022) were processed on the Google Earth Engine (GEE) platform, followed by feature selection and classification using the Random Forest (RF) algorithm. …”
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RLK-YOLOv8: multi-stage detection of strawberry fruits throughout the full growth cycle in greenhouses based on large kernel convolutions and improved YOLOv8 by Lei He, Lei He, Lei He, Dasheng Wu, Dasheng Wu, Dasheng Wu, Xinyu Zheng, Xinyu Zheng, Xinyu Zheng, Fengya Xu, Fengya Xu, Fengya Xu, Shangqin Lin, Shangqin Lin, Shangqin Lin, Siyang Wang, Siyang Wang, Siyang Wang, Fuchuan Ni, Fang Zheng

“…Compared to the baseline YOLOv8, the proposed algorithm demonstrates a 3.3% improvement in detection accuracy under complex backgrounds and dense multi-target scenarios.DiscussionThe RLK-YOLOv8 exhibits outstanding performance in strawberry multi-stage detection and yield estimation tasks, validating the effectiveness of integrating large kernel convolutions and multi-scale feature fusion strategies. …”
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Potato precision planter metering system based on improved YOLOv5n-ByteTrack by Cisen Xiao, Changlin Song, Junmin Li, Min Liao, Yongfan Pu, Kun Du

“…To address this issue, this study proposes a detection algorithm for the potato planting machine’s seed potato scooping scene, based on an improved lightweight YOLO v5n model. …”
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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

“…Addressing the issue of ''qualified environmental parameters but chicken discomfort'' caused by traditional methods overlooking spatial heterogeneity and individual differences, a dynamic ventilation quality assessment method based on panting behavior detection in laying hens was proposed. The YOLOv10-BCE panting behavior detection model was developed by embedding the BiFormer module into the backbone network to enhance multi-dimensional feature extraction, compressing neck structure parameters using the C3Ghost module, and integrating Efficient Intersection over Union (EIOU) loss to improve detection accuracy and convergence speed. …”
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Learning-based early detection of post-hepatectomy liver failure using temporal perioperative data: a nationwide multicenter retrospective study in ChinaResearch in context by Kai Wang, Qian Yang, Kang Li, Shanhua Tang, Baoluhe Zhang, Xiangyun Liao, Shunda Du, Wenguang Fu, Zhiwei Li, Huanwei Chen, Haorong Xie, Pengxiang Huang, Jieyuan Li, Qiuting Wang, Haiqing Liu, Zhiwei Huang, Pheng Ann Heng, Xueshuai Wan, Chuanjiang Li, Weixin Si

“…PHLF was diagnosed by concurrent elevated prothrombin time/INR and hyperbilirubinemia on or after postoperative day 5 and graded according to the International Study Group of Liver Surgery criteria. The proposed algorithm employed a powerful foundation model (Bio-Clinical Bidirectional Encoder Representation from Transformers) and a context-aware transformer module to perform in-depth temporal feature investigation of perioperative data to enable early detection of PHLF. …”
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Detection of Silent Type I Choroidal Neovascular Membrane in Chronic Central Serous Chorioretinopathy Using En Face Swept-Source Optical Coherence Tomography Angiography by Magdy Moussa, Mahmoud Leila, Hagar Khalid, Mohamed Lolah

“…A retrospective observational case series reviewing the clinical data, FFA, SS-OCT, and SS-OCTA images of patients with chronic CSCR, and comparing the findings. SS-OCTA detects the CNV complex and delineates it from the surrounding pathological features of chronic CSCR by utilizing the blood flow detection algorithm, OCTARA, and the ultrahigh-definition B-scan images of the retinal microstructure generated by swept-source technology. …”
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Improved machine learning framework for prediction of phases and crystal structures of high entropy alloys by Debsundar Dey, Suchandan Das, Anik Pal, Santanu Dey, Chandan Kumar Raul, Pritam Mandal, Arghya Chatterjee, Soumya Chatterjee, Manojit Ghosh

“…Among all these algorithms, XGBoost recorded the highest detection accuracy of 94.05 % for phases and LightGBM yielded the highest detection accuracy of 90.07 % for crystal structure. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Afterward, these distinguishing characteristics are harnessed to detect depression through the optimized PSO-SVM algorithm. …”
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A New Texture Aware—Seed Demand Enhanced Simple Non-Iterative Clustering (ESNIC) Segmentation Algorithm for Efficient Land Use and Land Cover Mapping on Remote Sensing Image... by Rohini Selvaraj, D. Geraldine Bessie Amali

“…Incorporating texture features extracted through the Gray-Level Co-occurrence Matrix along with spectral information in the proposed ESNIC segmentation algorithm improves the ability to distinguish between different LULC types that share the same spectral value. …”
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Applying interpretable machine learning to assess intraspecific trait divergence under landscape‐scale population differentiation by Sambadi Majumder, Chase M. Mason

“…Abstract Premise Here we demonstrate the application of interpretable machine learning methods to investigate intraspecific functional trait divergence using diverse genotypes of the wide‐ranging sunflower Helianthus annuus occupying populations across two contrasting ecoregions—the Great Plains versus the North American Deserts. Methods Recursive feature elimination was applied to functional trait data from the HeliantHOME database, followed by the application of the Boruta algorithm to detect the traits that are most predictive of ecoregion. …”
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sEMG-Based Control of Prosthesis Hand Using LSTM Classification and SMC by Amanual Tesfaye Takele, Dereje Shiferaw Negash

“…This increased the accuracy of the neural network from 52.3%, using raw data, to 99.7%, using extracted features. Once the required hand gesture was identified from the sEMG signal, interpretation of the gesture into individual fingers joint angles was done using cubic polynomial path-planning algorithm. …”
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Research on the Method of Crop Pest and Disease Recognition Based on the Improved YOLOv7-U-Net Combined Network by Wenchao Xiang, Zitao Du, Xinran Liu, Zehui Lu, Yuna Yin

“…For the U-Net network, the CBAM attention module is added before decoder skip connections, and depth-separable convolutions replace traditional kernels to strengthen feature fusion and detail attention. Experimental results show the improved algorithm achieves 97.49% detection accuracy, with mean average precision (mAP) reaching 96.91% and detection speed increasing to 90.41 FPS. …”
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Evaluation method of hydrophobicity of composite insulators based on improved Mask R-CNN by SHENG Fei, CAO Liu, LIU Yulong, HUANG Jie, HUANG Yaqian, ZHU Yanqing

“…In this paper, the classification problem is transformed into the target detection problem, and the improved mask region-based convolutional neural network (Mask R-CNN) algorithm is used to evaluate the hydrophobicity level of composite insulators. …”
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