Backdoor defense method in federated learning based on contrastive training by Jiale ZHANG, Chengcheng ZHU, Xiang CHENG, Xiaobing SUN, Bing CHEN

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Research on Sports Training Action Image Recognition Based on SDN by Dianhai Wang, Lianmei Shen

“…Extracting the neighborhood feature of sports training action, the recognition of sports training action image based on SDN architecture is completed. …”
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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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Physical function evaluation in volleyball training based on intelligent GRNN by Kaiyuan Dong, Borhannudin bin Abdullah, Hazizi bin Abu Saad, Chenxi Lu

“…Abstract This study aims to improve both the evaluation accuracy and the real-time feedback capability in monitoring athletes’ physical function changes during volleyball training. Firstly, based on the framework of the generalized regression neural network, a variable-structure generalized regression neural network (VSGRNN) is proposed and developed. …”
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Webshell malicious traffic detection method based on multi-feature fusion by Yuan LI, Yunpeng WANG, Tao LI, Baoqiang MA

“…Webshell is the most common malicious backdoor program for persistent control of Web application systems, which poses a huge threat to the safe operation of Web servers.For most Webshell detection method based on the request packet data for training, the method for web-based Webshell recognition effect is poorer, and the model of training efficiency is low.In response to the above problems, a Webshell malicious traffic detection method based on multi-feature fusion was proposed.The method was characterized by the three dimensions of Webshell packet meta information, packet payload content and traffic access behavior.Combining domain knowledge, feature extraction of request and response packets in the data stream.Transformed into feature extraction information for information fusion, forming a discriminant model that could detect different types of attacks.Compared with the previous research method, the accuracy rate of the method here in the two classification of normal and malicious traffic has been improved to 99.25%.The training efficiency and detection efficiency have also been significantly improved, and the training time and detection time have been reduced by 95.73% and 86.14%.…”
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SIDH: A Game-Based Architecture for a Training Simulator by P. Backlund, H. Engström, M. Gustavsson, M. Johannesson, M. Lebram, E. Sjörs

“…These features are expected to enhance immersion and fidelity. …”
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ENGINEERING PEDAGOGY AS A BASE FOR TECHNICAL TEACHER TRAINING SYSTEM by V. V. KONDRATYEV

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Implementation of project-based training in the educational process of a university by Natalya Mikhailovna Suetina, Azamat Kaplanovich Temzokov

“…The article is devoted to studying the features of the implementation of project-based learning technology in the educational process of a university. …”
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Visualization of simulation-based training in otolaryngology: A bibliometric analysis by Wenqi Yang, Xiaowei Zhang, Yuzhe Kong, Jiayin Li, Ru Gao, Xiaohong Tang

“…Objectives: This study aims to comprehensively summarize the advancements and insights in simulation-based otolaryngology training, highlighting the growth trends, geographical distribution, institutional contributions, journal impacts, authorship patterns, reference co-citations, and keyword dynamics over the past two decades. …”
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Chinese Sequence Labeling Based on Stack Pre-training Model by LIU Yu-peng, LI Guo-dong

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Teachers' Perspective of Teaching Language Features in High School: A Qualitative Research by Pungky Ramadhani

“…The result of this study finds that the teacher understood the language features in a genre-based approach based on the curriculum. …”
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Intelligent classification models for food products basis on morphological, colour and texture features by Narendra Veernagouda Ganganagowder, Priya Kamath

“…., using digital images. The Correlation-based Feature Selection (CFS) algorithm and 2nd derivative pre-treatments of the Morphological, Colour and Texture features are used to train the models for classification and detection. …”
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Adaptive Track Association Method Based on Automatic Feature Extraction by Zhaoyue Zhang, Guanting Dong, Chenghao Huang

“…To achieve accurate identification and association between radar tracks and ADS-B tracks, this study proposes an adaptive feature extraction method based on the longest common subsequence (LCSS) combined with classification theory to address the limitations inherent in traditional machine learning-based track association approaches. …”
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Recognition of PQ stego images based on identifiable statistical feature by Ji-cang LU, Fen-lin LIU, Xiang-yang LUO, Yi ZHANG

“…A PQ (perturbed quantization) stego images recognition algorithm is proposed based on identifiable statistical feature. According to the specific changing ways of PQ steganography to image data, the proposed algorithm extracts the identifiable statistical feature that can distinguish PQ stego images from other types of stego images. …”
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Multi-adversarial domain adaptation method based on feature correction by Yong ZHANG, Haoshuang LIU, Qi ZHANG, Wenzhe LIU

“…Domain adaptation can transfer labeled source domain information to an unlabeled but related target domain by aligning the distribution of source domain and target domain.However, most existing methods only align the low-level feature distributions of the source and target domains, failing to capture fine-grained information within the samples.To address this limitation, a feature correction-based multi-adversarial domain adaptation method was proposed.An attention mechanism to highlight transferable regions was introduced in this method and a feature correction module was deployed to align the high-level feature distributions between the two domains, further reducing domain discrepancies.Additionally, to prevent individual classifiers from overfitting their own noisy pseudo-labels,dual classifier co-training was proposed and the feature aggregation property of graph neural networks was utilized to generate more accurate source domain labels.Extensive experiments on three benchmark datasets for transfer learning demonstrate the effectiveness of the proposed method.…”
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Learning Feature Fusion in Deep Learning-Based Object Detector by Ehtesham Hassan, Yasser Khalil, Imtiaz Ahmad

“…In this work, we present an object detection framework by learning-based fusion of handcrafted features with deep features. …”
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Cattle identification based on multiple feature decision layer fusion by Dongxu Li, Baoshan Li, Qi Li, Yueming Wang, Mei Yang, Mingshuo Han

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Multi-Feature Facial Complexion Classification Algorithms Based on CNN by Xiyuan Cao, Delong Zhang, Chunyang Jin, Zhidong Zhang, Chenyang Xue

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FAULT DIAGNOSIS BASED ON IMPROVED KFDA INDIVIDUAL FEATURE SELECTION by CHEN Rui

“…In order to diagnose fault effectively by using sensitive features contained in the feature set, KFDA was improved in this paper and a fault diagnosis method based on improved KFDA individual feature selection was proposed. …”
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Research on Sarcastic Emotion Recognition Based on Multiple Feature Fusion by Si Kaihao

“…The second model reviewed deploys a multi-head attention-based bidirectional LSTM architecture. This approach incorporates pre-trained word embeddings, multi-head attention mechanisms, and custom-crafted features to proficiently identify sarcasm in social media datasets. …”
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