A satellite navigation spoofing interference detection method based on LSTM by ZHAO Shen, HUANG Wenna, QIN Yemei, LIAO Yifei, YANG Lingling

“…Based on the analysis of the effect of spoofing interference on the receiver loop, the direct and indirect information in the tracking loop was selected as the spoofing detection feature parameters. …”
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Distinguishing Human Journalists from Artificial Storytellers Through Stylistic Fingerprints by Van Hieu Tran, Yakub Sebastian, Asif Karim, Sami Azam

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Automated Detection of Poor-Quality Scintigraphic Images Using Machine Learning by Anil K. Pandey, Akshima Sharma, Param D. Sharma, Chandra S. Bal, Rakesh Kumar

“…The principal component analysis (PCA) of all the images was performed and the first 32 principal components (PCs) were retained as feature vectors of the image. …”
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Changes in Histological Features, Apoptosis and Necroptosis, and Inflammatory Status in the Livers and Kidneys of Young and Adult Rats by Emine Rumeysa Hekimoğlu, Mukaddes Eşrefoğlu, Birsen Elibol, Seda Kırmızıkan

“…Results: The histological features of the livers and kidneys of the 6-week-old rats were consistent with healthy mammalian organ features, while some histological changes were detected in sections of the 10-month-old rats. …”
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Cells Grouping Detection and Confusing Labels Correction on Cervical Pathology Images by Wenbo Pang, Yi Ma, Huiyan Jiang, Qiming Yu

“…To address this issue, we perform a labels correction module with feature similarity by constructing feature centers for typical cells in each category. …”
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Immunization with Complete Freund’s Adjuvant Reveals Trained Immunity-like Features in A/J Mice by Kiruthiga Mone, Shraddha Singh, Fatema Abdullatif, Meghna Sur, Mahima T. Rasquinha, Javier Seravalli, Denise K. Zinniel, Indranil Mukhopadhyay, Raul G. Barletta, Teklab Gebregiworgis, Jay Reddy

“…Specifically, we observed an increased level of lactate, indicative of aerobic glycolysis, which is implicated in TI, and this was also detected in the IFA group. Fourth, epigenetic analysis revealed histone enrichment in the promoter region of TNF-α, in the CFA group, but to a lesser degree than the BCG group. …”
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An Efficient Deep Learning Approach for Malaria Parasite Detection in Microscopic Images by Sorio Boit, Rajvardhan Patil

“…<b>Objective:</b> This paper presents EDRI, which is a novel hybrid deep learning model that integrates multiple architectures for malaria detection from red blood cell images. The EDRI model is designed to capture diverse features and leverage multi-scale analysis. …”
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Performance of Machine Learning and Image Processing in Plant Leaf Disease Detection by Abu Sarwar Zamani, L. Anand, Kantilal Pitambar Rane, P. Prabhu, Ahmed Mateen Buttar, Harikumar Pallathadka, Abhishek Raghuvanshi, Betty Nokobi Dugbakie

“…Precision agriculture's automatic leaf disease detection system employs image acquisition, image processing, image segmentation, feature extraction, and machine learning techniques. …”
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Study on infrasonic leakage monitoring and signal processing for product oil pipeline by Yuanbo YIN, Yuxing LI, Wen YANG, Shu LU, Chen ZHANG, Cuiwei LIU, Kai YANG, Wuchang WANG

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A comprehensive survey on techniques, challenges, evaluation metrics and applications of deep learning models for anomaly detection by Mudita Kohli, Indu Chhabra

“…Analyzing network packets for identifying deviations from the standard behavior is called anomaly detection. Deep learning tools have emerged as a promising alternative over classical machine learning approaches due to their proficiency in feature modeling, appraise detection rate, and mirror cognitive development. …”
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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

“…The traditional malware detection method is highly dependent on professional knowledge and static analysis, so we used the Self-Attention with Gate mechanism (SAG) based on the Transformer to carry out feature extraction between the local and global features and filter irrelevant noise information, then extracted the long-distance dependency temporal sequence features by the BiGRU network, and obtained the classification results through the SoftMax classifier. …”
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University Media Content Detection and Classification Based on Information Fusion Algorithm by Shuntao Zhang, Qinglan Yu, Tianming Yang, Kai Peng

“…This essay mainly introduces the technology of university media content detection and classification based on information fusion algorithm and focuses on the application of university multimedia content detection, analysis, and understanding, to explore the image discrimination auxiliary attribute feature learning and content association prediction and classification. …”
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An automatic classification of breast cancer using fuzzy scoring based ResNet CNN model by Nisha Y., Jagadeesh Gopal

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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…Abstract This paper aims to solve the problem of the difficulty in balancing the model size and detection accuracy of the unmanned mining truck detection network in open-pit mines, as well as the problem that the existing model is not suitable for mining truck equipment. …”
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Detection of SSL/TLS protocol attacks based on flow spectrum theory by Shize GUO, Fan ZHANG, Zhuoxue SONG, Ziming ZHAO, Xinjie ZHAO, Xiaojuan WANG, Xiangyang LUO

“…Network attack detection plays a vital role in network security.Existing detection approaches focus on typical attack behaviors, such as Botnets and SQL injection.The widespread use of the SSL/TLS encryption protocol arises some emerging attack strategies against the SSL/TLS protocol.With the network traffic collection environment that built upon the implements of popular SSL/TLS attacks, a network traffic dataset including four SSL/TLS attacks, as well as benign flows was controlled.Considering the problems that limited observability of existing detection and limited separation of the original-flow spatiotemporal domains, a flow spectrum theory was proposed to map the threat behavior in the cyberspace from the original spatiotemporal domain to the transformed domain through the process of “potential change” and obtain the “potential variation spectrum”.The flow spectrum theory is based on a set of separable and observable feature representations to achieve efficient analysis of network flows.The key to the application of flow spectrum theory in actual cyberspace threat behavior detection is to find the potential basis matrix for a specific threat network flow under the condition of a given transformation operator.Since the SSL/TLS protocol has a strong timing relationship and state transition process in the handshake phase, and there are similarities between some SSL/TLS attacks, the detection of SSL/TLS attacks not only needs to consider timing context information, but also needs to consider the high-separation representation of TLS network flows.Based on the flow spectrum theory, the threat template idea was used to extract the potential basis matrix, and the potential basis mapping based on the long-short-term memory unit was used to map the SSL/TLS attack network flow to the flow spectrum domain space.On the self-built SSL/TLS attack network flow data set, the validity of the flow spectrum theory is verified by means of classification performance comparison, potential variation spectrum dimensionality reduction visualization, threat behavior feature weight evaluation, threat behavior spectrum division assessment, and potential variation base matrix heatmap visualization.…”
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ELNet: An Efficient and Lightweight Network for Small Object Detection in UAV Imagery by Hui Li, Jianbo Ma, Jianlin Zhang

“…To address this issue, we propose ELNet, an efficient and lightweight object detection model based on YOLOv12n. First, based on an analysis of UAV image characteristics, we strategically remove two A2C2f modules from YOLOv12n and adjust the size and number of detection heads. …”
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Image saliency detection in wavelet domain based on the contrast sensitivity function by Ying-chun GUO, Yan-hong FENG, Gang YAN, Ming YU

“…A method of high definition saliency detection based on contrast sensitive function and wavelet analysis was proposed in order to improve the resolution of saliency maps.Original image was filtered by contrast sensitive function in YCbCr space,which could simulate the contrast of human eyes; then wavelet decomposition was carried out in Y,Cb,and Cr three channels individually,low frequency and high frequency feature saliency maps were extracted and further combined to obtain saliency map in single channel; finally saliency maps in three channels were fused to the high resolution saliency map.Experiments result show that the saliency images have high resolution,well-defined boundaries,and whole highlight salient objects.…”
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Plant leaf disease detection using vision transformers for precision agriculture by Murugavalli S, Gopi R

“…In leaf image analysis, convolutional neural networks (CNNs) have revealed promise in leaf disease detection and classification. …”
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Detection of multiple pesticide residues on the surface of broccoli based on hyperspectral imaging by GUI Jiangsheng, GU Min, WU Zixian, BAO Xiao’an

“…To increase efficiency of the model and reduce the redundancy of the hyperspectral image, using the principal component analysis (PCA) algorithm and successive projection algorithm (SPA) for feature extraction. …”
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Incorporating exon–exon junction reads enhances differential splicing detection by Mai T. Pham, Michael J. G. Milevskiy, Jane E. Visvader, Yunshun Chen

“…This DEJU analysis workflow adopts a new feature quantification approach that jointly summarises exon and exon–exon junction reads, which are then integrated into the established Rsubread-edgeR/limma frameworks. …”
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