Deception detection based on micro-expression and feature selection methods by Shusen Yuan, Zilong Shao, Zhongjun Ma, Ting Cao, Hongbo Xing, Yong Liu, Yewen Cao

“…In this paper, a deception detection framework is proposed that incorporates a novel set of features and a unique deception detection method based on facial expressions, particularly micro-expressions. …”
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Named Entity Recognition Method Based on Multi-Feature Fusion by Weidong Huang, Xinhang Yu

“…Initially, the Non-negative Matrix Factorization (NMF) model is employed to perform thematic clustering on the review texts, and entity types are extracted based on the clustering results. Subsequently, we introduce an entity recognition model utilizing the pre-trained BERT model as an embedding layer, with BiLSTM and DGCNN incorporating residual connection and gating mechanisms as feature extraction layers. …”
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Episodic Training and Feature Orthogonality-Driven Domain Generalization for Rotating Machinery Fault Diagnosis Under Unseen Working Conditions by Yixiao Liao, Songbin Zhou, Yisen Liu, Kunkun Pang, Jing Li, Chang Li, Lulu Zhao

“…To address these limitations, an episodic training and feature orthogonality-driven domain generalization (EODG) method is proposed. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…During this training process, both agents calculate the reward value, update their respective strategies, and transfer parameters based on the classification results. …”
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Feature extraction and classification of digital rock images via pre-trained convolutional neural network and unsupervised machine learning by Masashige Shiga, Masao Sorai, Tetsuya Morishita, Masaatsu Aichi, Naoki Nishiyama, Takashi Fujii

“…Using pre-trained CNNs allows us to extract rich feature representations without the need for large, specialized training datasets, effectively capturing intricate patterns in the microstructures. …”
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Software Defect Prediction Based on Effective Fusion of Multiple Features by Chaozheng Zhang, Junhua Wu

“…Traditional software defect prediction models typically rely on a single feature or perform simple aggregation of multiple features during training. …”
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Virtual Reality Video Image Classification Based on Texture Features by Guofang Qin, Guoliang Qin

“…Therefore, this article proposes a dense convolutional neural network classification algorithm based on texture features for images in virtual reality videos. …”
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Multi-scale feature fusion keypoint detection network for ship draft line localization by Bo Zhang, Yumengmeng Yin, Kefu Ma, Hong Wang

“…To enhance the model’s adaptability to various environmental conditions, we adopt a dual-phase training strategy: an initial pre-training phase for learning general ship features and waterline characteristics, followed by a fine-tuning phase using data from diverse scenes. …”
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Feature Attention Cycle Generative Adversarial Network: A Multi-Scene Image Dehazing Method Based on Feature Attention by Na Li, Na Liu, Yanan Duan, Yuyang Chai

“…The generator structure is improved based on the CycleGAN model, and a feature fusion attention module is proposed. …”
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Specific features of designing a database for neuro-oncological 3D MRI images to be used in training artificial intelligence by E. V. Amelina, A. Yu. Letyagin, B. N. Tuchinov, N. Yu. Tolstokulakov, M. E. Amelin, E. N. Pavlovsky, V. V. Groza, S. K. Golushko

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Seam-Carving forgery detection based on expanded Markov features by Guo-rui SHENG, Tie-gang GAO, Li FAN, Lin GAO, Fu-sheng YANG, Shun ZHANG

“…To deal with the digital image forgery using Seam-Carving, a detection algorithm based on expanded Markov features was proposed. The algorithm takes full acount of the image frequency domain change caused by Seam-Carving operation, merges the features based on traditional and expands Markov transfer-probability matrix. …”
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Predicting Mental and Neurological Illnesses Based on Cerebellar Normative Features by Milin Kim, Nitin Sharma, Esten H. Leonardsen, Saige Rutherford, Geir Selbæk, Karin Persson, Nils Eiel Steen, Olav B. Smeland, Torill Ueland, Geneviève Richard, Aikaterina Manoli, Sofie L. Valk, Dag Alnæs, Christian F. Beckman, Andre F. Marquand, Ole A. Andreassen, Lars T. Westlye, Thomas Wolfers, Torgeir Moberget

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Electrogastrogram-based detection of cybersickness with the application of wavelet transformation and machine learning: A case study by Ilija V. Tanasković, Nenad B. Popović, Jaka J. Sodnik, Sašo J. Tomažič, Nadica S. Miljković

“…Furthermore, recovery signs appear approximately 8 minutes after the first VR experience supporting the idea of conducting multiple sessions the same day i.e., intensive VR-based training. Conclusions: The unsupervised ML shows potential in identifying CSaffected EGG signal segments with feature extraction based on DWT, offering a novel approach for enhancing the prevention of CS occurrence in VR-based military training and other VR-related environments.…”
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FEATURES OF DEVELOPMENT AND APPLICATION OF AEROBICS IN THE SYSTEM OF PHYSICAL EDUCATION by Shuba Liudmyla, Shuba Victor, Shuba Victoria

“…Meanwhile, certain negative consequences that may arise from improper organization of aerobics classes have been identified, including the risk of injury, overloading the cardiovascular system, the necessity of adhering to proper technique, and psychological stress. The characteristic features of modern health aerobics are: accessibility and ease of performing exercises; increased emotionality of classes due to musical accompaniment and different movements; high effectiveness of the health-improving effect due to the continuity of physical exercises aimed at the development of general endurance, flexibility and strength, as well as improving the work of the cardiovascular, respiratory systems and musculoskeletal system; a high level of scientific substantiation of training methods, constant development of the material and technical base and development of new types of equipment for aerobics. …”
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Intrusion Detection System Framework for SDN-Based IoT Networks Using Deep Learning Approaches With XAI-Based Feature Selection Techniques and Domain-Constrained Features by Manlaibaatar Tserenkhuu, Md Delwar Hossain, Yuzo Taenaka, Youki Kadobayashi

“…Our study provides guidelines for selecting suitable XAI-based feature selection techniques that incorporate domain-constrained features in the development of IDSs for SDN-based IoT networks.…”
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Transfer learning based hybrid feature learning framework for enhanced skin cancer diagnosis using deep feature integration by Maridu Bhargavi, Sivadi Balakrishna

“…To address these issues, this research proposes the DRMv2Net model, a feature fusion deep learning-based technique that integrates multiple pre-trained convolutional neural networks to enhance skin cancer diagnosis. …”
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Precise Crop Pest Detection Based on Co-Ordinate-Attention-Based Feature Pyramid Module by Chenrui Kang, Lin Jiao, Kang Liu, Zhigui Liu, Rujing Wang

“…Therefore, to overcome these limitations, we first designed a co-ordinate-attention-based feature pyramid network, termed CAFPN, to extract the salient visual features that distinguish small insects from each other. …”
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Design of On-board Long-range Perception System for Train by HUANG Wenyu, PAN Wenbo, LI Yuanzhengyu, CHEN Zhiwei, YANG Zhenyu, YUAN Chao

“…This system is equipped with a set of high-resolution long-range millimeter-wave radars that are adaptable to the strong scattering environment of rail transit and features an accurate method of calculating train speed based on the region of interest and the continuity hypothesis of speed. …”
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Research on Classification of Rail Defects Based on Image Processing Algorithm by Mengying HUANG, Jiangping LUO, Wenxing WANG, Jingwei CAO

“…Secondly, the feature vectors of different kinds of defects were trained by support vector machine, and the optimal classification function was obtained. …”
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Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…A fusion strategy is then used to compensate for interval discontinuities, enabling accurate characterization of clutter properties in the current maritime environment. Based on the characterized clutter properties, a hybrid feature selection strategy is further proposed to construct a diverse and compact training sample set by integrating global density distribution with local gradient variation. …”
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