A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…With the popularization of smart terminals and the gradual increase of power grid informatization and digitization, the protection of power monitoring systems from various cybersecurity threads is a current scientific problem that needs to be solved urgently. To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
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A Novel Quadrilateral Contour Disentangled Algorithm for Industrial Instrument Reading Detection by Xiang Li, Changchang Zeng, Yong Yao, Jide Qian, Haiding Zhang, Sen Zhang, Suixian Yang

“…First, a Multi-scale Feature Pyramid Network (MsFPN) is proposed for effective feature extraction to improve model accuracy. …”
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Research on Remaining Useful Life Prediction of Control Rod Drive Mechanism Rotor Components in Floating Nuclear Reactor by Liming Zhang, Chen Wang, Ling Chen, Tian Tan, Luqi Liao

“…At the same time, the time-frequency domain feature analysis is carried out on the original vibration data, and the changing trends of the extracted features are carefully analyzed. …”
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Infrared small target detection algorithm with U-shaped multiscale transformer network by DUAN Peipei, ZHANG Yan, LUO Mingshi, YAN Xiaoying

“…To solve the problem of small targets feature extraction and the susceptibility of targets to being overwhelmed by noise and complex backgrounds, a detection method with U-shaped multiscale transformer network is proposed. …”
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Cross-View Geo-Localization: A Survey by Abhilash Durgam, Sidike Paheding, Vikas Dhiman, Vijay Devabhaktuni

“…This paper provides a thorough survey of cutting-edge methodologies, techniques, and associated challenges that are integral to this domain, with a focus on feature-based and deep learning strategies. Feature-based methods capitalize on unique features to establish correspondences across disparate viewpoints, whereas deep learning-based methodologies deploy neural networks (convolutional or transformer-based) to embed view-invariant attributes. …”
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Detection of cervical cell based on multi-scale spatial information by Gang Li, Xinyu Fan, Chuanyun Xu, Pengfei Lv, Ru Wang, Zihan Ruan, Zheng Zhou, Yang Zhang

“…To tackle this problem effectively, we propose a cervical cell detection method that utilizes multi-scale spatial information. …”
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Hybrid CNN-based Recommendation System by Muhammad Alrashidi, Roliana Ibrahim, Ali Selamat

“… Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. …”
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A Deep Neural Network Framework for Dynamic Two-Handed Indian Sign Language Recognition in Hearing and Speech-Impaired Communities by Vaidhya Govindharajalu Kaliyaperumal, Paavai Anand Gopalan

“…In order to improve both model generalization and image quality, preprocessing is applied to images prior to prediction, and the proposed dataset is organized to handle multiple dynamic words. Feature graining is employed to obtain local features, and the ViT transformer architecture is then utilized to capture global features from the preprocessed images. …”
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Mean Shift Fusion Color Histogram Algorithm for Nonrigid Complex Target Tracking in Sports Video by Yu Liu, Xiaoyan Wang

“…The multiple hypothesis target tracking algorithms are used to track multiple targets, while the chunking feature is used to solve the problem of mutual occlusion and adhesion between targets. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…Our proposed self-ensemble learning framework, which utilizes a single feature extractor, simplifies this process by alternately training multiple classifiers with shared feature extractors. …”
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RGB-D salient object detection based on BC2 FNet network by WANG Feng, CHENG Yongmei

“…Secondly, a boundary-driven feature selection module is designed, which is dedicated to simultaneously focusing on important feature information and preserving boundary details in the process of RGB and depth modality fusion. …”
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InGSA: integrating generalized self-attention in CNN for Alzheimer's disease classification by Faisal Binzagr, Anas W. Abulfaraj

“…However, such traditional methods involve depending on feature extraction that is usually complex, time-consuming, and requiring substantial effort from the medical personnel. …”
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Salient object detection dataset with adversarial attacks for genetic programming and neural networksMendeley Data by Matthieu Olague, Gustavo Olague, Roberto Pineda, Gerardo Ibarra-Vazquez

“…Machine learning is central to mainstream technology and outperforms classical approaches to handcrafted feature design. Aside from its learning process for artificial feature extraction, it has an end-to-end paradigm from input to output, reaching outstandingly accurate results. …”
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Detection of the Pin Defects of Power Transmission Lines Based on Improved TPH-MobileNetv3 by Mengxuan Li, Jingshan Han, Zhi Yang, Bin Zhao, Peng Liu

“…Given the small size of a pin and many similar components, the detection of such defects is not ideal, which is a technological problem in the identification and diagnosis of power defects. …”
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Contrastive learning enhanced pseudo-labeling for unsupervised domain adaptation in person re-identification. by Xuemei Bai, Yuqing Zhang, Chenjie Zhang, Zhijun Wang

“…We first enhance the feature representation of the target domain samples based on the contrast learning technique to improve their discrimination in the feature space, thereby enhancing the cross-domain migration performance of the model. …”
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Intelligent library shelf management system for open-access environments: A CNN-based approach with enhanced image recognition and disorder detection by Xueqi Zhang

“…The study is conducted to solve the problem of unorganized placement of books faced by traditional library management systems in an open-shelf lending environment. …”
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Ensemble machine learning-based pre-trained annotation approach for scRNA-seq data using gradient boosting with genetic optimizer by Osama Elnahas, Waleed M. Ead, Yushan Qiu, Jian Lu

“…We propose an ensemble machine learning-based pre-trained annotation framework that integrates gradient boosting and genetic optimization for robust feature selection. The proposed method uses ensemble learning to enhance annotation accuracy under data scarcity, addressing limitations in existing supervised methods by leveraging a combination of multiple annotated datasets and feature alignment strategies. …”
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Incorporating Attention Mechanism Into CNN-BiGRU Classifier for HAR by Ohoud Nafea, Wadood Abdul, Ghulam Muhammad

“…Automatic high-level feature extraction has become possible using deep learning to optimize performance. …”
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Robust two stages federated learning for sensor based human activity recognition with label noise by Haifeng Sun, Junping Yao, Xiaojun Li, Yanfei Liu, Hongyang Gu

“…To overcome these challenges of complex label noise and feature drift, this paper proposes LN-FHAR, a two-stage federated learning framework with label noise robustness. …”
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GSB: GNGS and SAG-BiGRU network for malware dynamic detection. by Zhanhui Hu, Guangzhong Liu, Xinyu Xiang, Yanping Li, Siqing Zhuang

“…However, the minority categories' attacks will bring great losses to countries, enterprises, or individuals. For solving the problem, this study proposed the GNGS algorithm to construct a new balance dataset for the model algorithm to pay more attention to the feature learning of the minority attacks' malware to improve the detection rate of attacks' malware. …”
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