Stealthy graph backdoor attack based on feature trigger by Yang Chen, Zhou Bin, Haixing Zhao

“…To solve this problem, we propose a novel graph Backdoor Attack based on Feature Trigger (BAFT). …”
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Analysis of super-long and sparse feature in pseudo-random sequence based on similarity by Chun-jie CAO, Jing-zhang SUN, Zhi-qiang ZHANG, Long-juan WANG, Meng-xing HUANG

“…Similarity analysis of pseudo-random sequence in wireless communication networks is a research hotspot problem in the domain of information warfare.Based on the difficulties in super-long sequence,extremely sparse feature,and futilities in engineering application for real-time processing exist in similarity analysis of sequence in wireless net-work,a method of similarity analysis of sequence in a certain margin of misacceptance probability was proposed.Firstly,the similarity probability distribution of real-random sequence was theoretically analyzed.Secondly,according to the standard of NIST SP 800-22,the randomness of pseudo-bitstream was analyzed and the validity of pseudo-bitstream was judged.Finally,similarity was analyzed and verified by combining super-long pseudo-random sequence in real wireless communication networks.The results indicate that the lower bound of similarity value is 0.62 when misacceptance prob-ability uncertainty at about 1%.Above conclusion is considerable importance from the significance and theoretical values in network security domains,such as protocol analysis,traffic analysis,intrusion detection and others.…”
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Evaluation of Key Remote Sensing Features for Bushfire Analysis by Ziyi Yang, Husam Al-Najjar, Ghassan Beydoun, Bahareh Kalantar, Mohsen Zand, Naonori Ueda

“…This study evaluates remote sensing features to resolve problems associated with feature redundancy, low efficiency, and insufficient input feature analysis in bushfire detection. …”
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An Effective Feature Extraction Method for Tomato Leafminer - Tuta Absoluta (Meyrick) (Lepidoptera: Gelechiidae) Classification by Tahsin Uygun, Serhat Kiliçarslan, Cemil Közkurt, Mehmet Metin Ozguven

“…These results highlight the potential of combining deep learning-based feature extraction with conventional machine learning for early pest detection. …”
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Epidemiological Features of Sexually Transmitted Infections in the Republic of Tatarstan by Zh. G. Eremeeva, R. Z. Ibragimova, S. T. Agliullina

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Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

“…Aiming at the problems of insufficient detection accuracy and high false detection rates of traditional pest detection models in the face of small targets and incomplete targets, this study proposes an improved target detection network, I-YOLOv10-SC. …”
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Learning Feature Fusion in Deep Learning-Based Object Detector by Ehtesham Hassan, Yasser Khalil, Imtiaz Ahmad

“…Object detection in real images is a challenging problem in computer vision. …”
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Ensemble Classifiers and Feature-Based Methods for Structural Damage Assessment by Hossein Babajanian Bisheh, Gholamreza Ghodrati Amiri, Ehsan Darvishan

“…In this paper, a new structural damage detection framework is proposed based on vibration analysis and pattern recognition, which consists of two stages: (1) signal processing and feature extraction and (2) damage detection by combining the classification result. …”
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Android collusion attack detection model by Hongyu YANG, Zaiming WANG

“…In order to solve the problem of poor efficiency and low accuracy of Android collusion detection,an Android collusion attack model based on component communication was proposed.Firstly,the feature vector set was extracted from the known applications and the feature vector set was generated.Secondly,the security policy rule set was generated through training and classifying the privilege feature set.Then,the component communication finite state machine according to the component and communication mode feature vector set was generated,and security policy rule set was optimized.Finally,a new state machine was generated by extracting the unknown application’s feature vector set,and the optimized security policy rule set was matched to detect privilege collusion attacks.The experimental results show that the proposed model has better detective efficiency and higher accuracy.…”
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MP-NER: Morpho-Phonological Integration Embedding for Chinese Named Entity Recognition by Pu Li, Guopeng Cheng, Guojun Deng, Shuanghong Qu, Min Huang, Guoxiang Li

“…Additionally, the lack of clear separators between Chinese characters exacerbates these challenges, leading to difficulties in boundary detection and entity category determination. Inspired by the hieroglyphic and phonetic features of Chinese characters, this study proposes a multi-feature fusion embedding model (MP-NER). …”
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Workflow Detection with Improved Phase Discriminability by ZHANG, M., HU, H., LI, Z.

“…Workflow detection is a challenge issue in the process of Industry 4.0, which plays a crucial role in intelligent production. …”
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MFAN: Multi-Feature Attention Network for Breast Cancer Classification by Inzamam Mashood Nasir, Masad A. Alrasheedi, Nasser Aedh Alreshidi

“…Despite various AI-based strategies in the literature, similarity in cancer and non-cancer regions, irrelevant feature extraction, and poorly trained models are persistent problems. …”
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Explainability Feature Bands Adaptive Selection for Hyperspectral Image Classification by Jirui Liu, Jinhui Lan, Yiliang Zeng, Wei Luo, Zhixuan Zhuang, Jinlin Zou

“…Hyperspectral remote sensing images are widely used in resource exploration, urban planning, natural disaster assessment, and feature classification. Aiming at the problems of poor interpretability of feature classification algorithms for hyperspectral images, multiple feature dimensions, and difficulty in effectively improving classification accuracy, this paper proposes a feature band adaptive selection method for hyperspectral images. …”
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An Interpretability Method for Broken Wire Detection by Hailong Wu, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Mengpeng Qian, Xiaolin Yuan, Yong Wang

“…Therefore, it is necessary to perform broken wire detection. Deep learning has powerful feature-learning capabilities and is characterized by high accuracy and efficiency, and the YOLOv8 object detection model has been adopted to detect wire breaks in electromagnetic signal images of wire rope, achieving better results. …”
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Environmental Monitoring Smart System with Self-Sustaining Wireless Sensor Network Using Data Validation Algorithms by Kanwal T., Altaf S., Javed M. K.

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Medical Image Fusion Based on Feature Extraction and Sparse Representation by Yin Fei, Gao Wei, Song Zongxi

“…SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. …”
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Automatic picking method for ground penetrating radar wave groups at rough coal-rock interfaces by Ying TIAN, Chunzhi LI, Shuo CHEN, Zihao WANG, Fuyan LYU, Qiang ZHANG, Meng HAN, Chengjun HU

“…Forward modeling and experimental results show that this method can accurately detect the position of rough coal-rock interfaces. …”
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Driving Detection Based on the Multifeature Fusion by Qiufen Yang, Yan Lu

“…In order to solve the problems of facial feature localization and driver fatigue state identification methods in driving fatigue detection, a driving detection method based on the multifeature fusion was proposed. …”
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RGB-T Object Detection With Failure Scenarios by Qingwang Wang, Yuxuan Sun, Yongke Chi, Tao Shen

“…This article proposes a multimodal object detection method named diffusion enhanced object detection network (DENet), aiming to address modality failure problems caused by nonroutine environments, sensor anomalies, and other factors, while suppressing redundant information in multimodal data to improve model accuracy. …”
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FEATURES OF THE SCHEMES OF CASH PAYMENTS AND BANKING OPERATIONS WITH MONEY LAUNDERING by Irina N. Mihailova

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