Multipath and Deep Learning-Based Detection of Ultra-Low Moving Targets Above the Sea by Zhaolong Wang, Xiaokuan Zhang, Weike Feng, Binfeng Zong, Tong Wang, Cheng Qi, Xixi Chen

“…Finally, the RD features of the generalized target are learned by training the DL-based target detector, such as you-only-look-once version 7 (YOLOv7) and Faster R-CNN. …”
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Research on Sleep Staging Based on Support Vector Machine and Extreme Gradient Boosting Algorithm by Wang Y, Ye S, Xu Z, Chu Y, Zhang J, Yu W

“…Yiwen Wang,1 Shuming Ye,2 Zhi Xu,3 Yonghua Chu,1 Jiarong Zhang,4 Wenke Yu5 1Clinical Medical Engineering Department, The Second Affiliated Hospital, Zhejiang University School of Medicine, HangZhou, ZheJiang, People’s Republic of China; 2Department of Biomedical Engineering, Zhejiang University, HangZhou, ZheJiang, People’s Republic of China; 3China Astronaut Research and Training Center, BeiJing, People’s Republic of China; 4Baidu Inc, BeiJing, People’s Republic of China; 5Radiology Department, ZheJiang Province Qing Chun Hospital, HangZhou, ZheJiang, People’s Republic of ChinaCorrespondence: Yiwen Wang; Shuming Ye, Email karenkaren2010@zju.edu.cn; ysmln@vip.sina.comPurpose: To develop a sleep-staging algorithm based on support vector machine (SVM) and extreme gradient boosting model (XB Boost) and evaluate its performance.Methods: In this study, data features were extracted based on physiological significance, feature dimension reduction was performed through appropriate methods, and XG Boost classifier and SVM were used for classification. …”
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A BEARING DEEP LEARNING TRANSFER DIAGNOSIS METHOD BASED ON OPTIMIZATION OF SYMMETRIC POLAR COORDINATES by WU DingHai, WANG HuaiGuang, SONG Bin, ZHANG YunQiang

“…Aiming at the problem of graphical feature representation of one-dimensional mechanical vibration signals, a bearing fault diagnosis method based on symmetric polar coordinates and residual network migration learning is proposed, which combines the powerful image classification and recognition ability of convolution neural network. …”
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TDA SegUNet: Topological Data Analysis-Based Shape-Aware Brain Tumor Segmentation by Ansar Rahman, Ayesha Satti, Ahmad Raza Shahid, Qaisar M. Shafi, Khadija Farooq, Asad Ali Safi

“…TDA-SegUNet is a U-Net-based segmentation model that integrates topological data analysis (TDA) to extract shape-based local and global features from MRI scans. …”
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Cross-domain autonomous driving visual segmentation based on enhanced target data learning by Chaoyu Rao, Xiaoyong Fang, Yunzhe Zhang, Wanshu Fan, Dongsheng Zhou

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Construction of a prediction model for peripheral lymph node metastasis in patients with colorectal cancer based on enhanced CT texture features by Feng Tong, Longfei Zhang, Xiaobin Jiang, Zhenyu Wu

“…Abstract Background To investigate the analysis of peripheral lymph node metastasis prediction model construction for patients with colorectal cancer based on enhanced CT texture features. Methods In this study, the clinical data of 200 colorectal cancer patients admitted to our hospital from January 2019 to October 2024 were collected, which were divided into a training set (n = 140) and a validation set (n = 60) according to a 7:3 ratio. …”
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SCF-CIL: A Multi-Stage Regularization-Based SAR Class-Incremental Learning Method Fused with Electromagnetic Scattering Features by Yunpeng Zhang, Mengdao Xing, Jinsong Zhang, Sergio Vitale

“…This method offers three main contributions. First, for the feature extractor, we fuse the convolutional neural network features with the scattering center features using a cross-attention feature fusion structure, ensuring both the plasticity and stability of the extracted features. …”
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Motor imagery-based brain-computer interfaces: an exploration of multiclass motor imagery-based control for Emotiv EPOC X by Paulina Tarara, Iwona Przybył, Julius Schöning, Artur Gunia

“…Machine learning techniques were applied to extract discriminative features from the EEG signals.ResultsPost-training assessments indicated modest improvements in participants' MI proficiency. …”
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Multi-Level Feature Fusion in CNN-Based Human Action Recognition: A Case Study on EfficientNet-B7 by Pitiwat Lueangwitchajaroen, Sitapa Watcharapinchai, Worawit Tepsan, Sorn Sooksatra

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Prediction of Neoadjuvant Chemoradiotherapy Sensitivity in Patients With Esophageal Squamous Cell Carcinoma Using CT-Based Radiomics Combined With Clinical Features by Xindi Li, Jigang Dong, Baosheng Li, Ouyang Aimei, Yahong Sun, Xia Wu, Wenjuan Liu, Ruobing Li, Zhongyuan Li, Yu Yang

“…Objective: This study aimed to establish a predictive model, based on computed tomography (CT) radiomics features and clinical parameters, to predict sensitivity to nCRT in patients with ESCC pre-treatment. …”
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Establishment and validation of a combined diagnostic model for aldosterone-producing adenoma of the adrenal gland based on CT radiomics and clinical features by ZHANG Mingquan, LIU Jingjing, LIN Xin, FU Min, FENG Ying, CHEN Jingjing

“…Objective To establish a combined diagnostic model based on CT radiomics and clinical features, and to investigate the value of the model in the diagnosis of aldosterone-producing adenoma (APA) of the adrenal gland. …”
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Wind during terrestrial laser scanning of trees: Simulation-based assessment of effects on point cloud features and leaf-wood classification by W. Albert, H. Weiser, H. Weiser, R. Tabernig, R. Tabernig, B. Höfle, B. Höfle

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Adaptive evaluation of gross total resection rates for endoscopic endonasal approach based on preoperative MRI morphological features of pituitary adenomas by Ao Shen, Yue Min, Dongjie Zhou, Lirui Dai, Liang Lyu, Wenyi Zhan, Shu Jiang, Peizhi Zhou

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Detection of Typical Transient Signals in Water by XGBoost Classifier Based on Shape Statistical Features: Application to the Call of Southern Right Whale by Zemin Zhou, Yanrui Qu, Boqing Zhu, Bingbing Zhang

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HCT-Det: A High-Accuracy End-to-End Model for Steel Defect Detection Based on Hierarchical CNN–Transformer Features by Xiyin Chen, Xiaohu Zhang, Yonghua Shi, Junjie Pang

“…This structure combines window-based self-attention (WSA) blocks to reduce computational overhead and parallel residual convolutional (Res) blocks to enhance local feature continuity. …”
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Evolving Many-Objective Job Shop Scheduling Dispatching Rules via Genetic Programming With Adaptive Search Based on the Frequency of Features by Atiya Masood, Mansoor Ebrahim, Fahad Najeeb, Syed Muhammad Daniyal

“…In addition, relevant features are selected based on their frequency of occurrence in diverse sets of best individuals. …”
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CT-based radiomics features for the differential diagnosis of nodular goiter and papillary thyroid carcinoma: an analysis employing propensity score matching by Haiming Zhang, Zhenyu Li, Fengtao Zhang, Hengguo Li

“…PurposeThis study aims to evaluate the effectiveness of CT-based radiomics features in discriminating between nodular goiter (NG) and papillary thyroid carcinoma (PTC).MethodsA retrospective cohort comprising 228 patients with nodular goiter (NG) and 227 patients with papillary thyroid carcinoma (PTC) diagnosed between January 2018 and December 2022 was consecutively enrolled. …”
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Transformer-based multiple instance learning network with 2D positional encoding for histopathology image classification by Bin Yang, Lei Ding, Jianqiang Li, Yong Li, Guangzhi Qu, Jingyi Wang, Qiang Wang, Bo Liu

“…Furthermore, TMIL divides histopathological images into pseudo-bags and trains patch-level feature vectors with deep metric learning to enhance classification performance. …”
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Automated System Using HMM for Lung Disease Recognition Based on Cough Sounds by Shing-Tai Pan, Bo-Kai Lee, You-Qian Wu

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Assessment model of ozone pollution based on SHAP-IPSO-CNN and its application by Xiaolei Zhou, Xingyue Wang, Ruifeng Guo

“…Finally, the IPSO algorithm is combined with SHAP analysis to dynamically adjust the training features to optimize the performance of the CNN model. …”
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