Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models by Rijvan Beg, R. K. Pateriya, Deepak Singh Tomar

“…In the evolving cyber threat landscape, one of the most visible and pernicious challenges is malware activity detection and analysis. Traditional detection and analysis methods face threats of data high-dimensionality, lack of strength against adversarial attacks, and non-efficient use of unlabeled data samples. …”
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Improving Wind Turbine Gearbox Reliability: A Hybrid Deep Learning Approach Using Bispectrum Image Analysis by Muhammad Zacky Asy'Ari, Jun Kondoh, Benyamin Kusumoputro

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An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures by Andrzej D. Dobrzycki, Ana M. Bernardos, José R. Casar

“…The You Only Look Once (YOLO) architecture is crucial for real-time object detection. However, deploying it in resource-constrained environments such as unmanned aerial vehicles (UAVs) requires efficient transfer learning. …”
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MRI features of AIDS with neurosyphilis by Mei-Ji REN, Li LI, Jing ZHAO, Hong-Jun LI

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Red-KPLS Feature Reduction with 1D-ResNet50: Deep Learning Approach for Multiclass Alzheimer’s Staging by Syrine Neffati, Ameni Filali, Kawther Mekki, Kais Bouzrara

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Analysis of Mini-Camera's Cat-Eye Retro-Reflection for Characterization of Diffraction Rings and Arrayed Spots by Chun Liu, Changming Zhao, Haiyang Zhang, Zilong Zhang, Shuyuan Gao, Yunshi Wang

“…The simulated and experimental results have good similarity in terms of profile shapes and trends with different incident angles and defocus distances. An analysis of the detection conditions and the reflection image features described in this article can thus be applied to hidden camera detection. …”
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Clinicopathological analysis of adrenal intravascular large B-cell lymphoma by LIN Jiaxin, WEI Ran, SHUI Ruohong, LU Hongfen, LI Xiaoqiu, YU Baohua

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Research on multi dimensional feature extraction and recognition of industrial and mining solid waste images based on mask R-CNN and graph convolutional networks by Shuqin Wang, Na Cheng, Yan Hu

“…The graph structure was input into GCN for high-order feature extraction, where the neighbor information of nodes was aggregated through multi-layer graph convolution to update node features, ultimately fusing the high-order features and primary features output by GCN to obtain multidimensional features for classification, detection, and segmentation tasks, thereby improving the accuracy and efficiency of image analysis. …”
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Study of anatomy-diagnostic features of leaves of <i>Cynara scolymus</i> L. grown under the conditions of the Kyrgyz Republic by S. C. Chubakova, N. T. Farmanova, N. V. Bobkova, T. A. Mamatov

“….), collected in the flowering phase (June) of 2023, in the Osh region of the Kyrgyz Republic, were used as the object of the study. To detect characteristic external features of artichoke prickly leaves, an external examination of the analytical sample was carried out visually (10 × ). …”
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GlassBoost: A Lightweight and Explainable Classification Framework for Tabular Datasets by Ehsan Namjoo, Alison N. O’Connor, Jim Buckley, Conor Ryan

“…To evaluate the system, we apply it to an anomaly detection task in the context of intrusion detection systems (IDSs), using a dataset containing traffic features from both malicious and normal activities. …”
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Attention-driven hybrid deep learning and SVM model for early Alzheimer’s diagnosis using neuroimaging fusion by Arjun Kidavunil Paduvilan, Godlin Atlas Lawrence Livingston, Sampath Kumar Kuppuchamy, Rajesh Kumar Dhanaraj, Muthuvel Subramanian, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

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Integration of Convolutional Neural Network and Image Processing for Pulp Fibril Detection and Measurement by Tanachot Chirakitsakul, Pakaket Wattuya, Phichit Somboon, Panthira Jansakra, Chakrit Watcharopas

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Clinical profile and molecular genetic analysis of alport syndrome in children: a single center experience by Aqsa Ahmad, Aqsa Ahmad, Liang Lijun, Zhang Yan, Zhang Yan, Ma Yan, Zhao Shuai, Zhao Shuai, Du Wangnan, Du Wangnan

“…Nine different variants were detected, with 3 mutations identified as novel. Two cases underwent histopathological analysis, revealing a thin basement membrane and mild to moderate mesangial proliferation. …”
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Deep multi-view feature fusion with data augmentation for improved diabetic retinopathy classification by Boualleg Yaakoub, Daouadi Kheir Eddine, Guehairia Oussama, Djeddi Chawki, Cheddad Abbas, Siddiqi Imran, Bouderah Brahim

“…This study introduces a novel framework for DR classification that leverages multi-view deep features, multilinear whitened principal component analysis, tensor exponential discriminant analysis, synthetic minority oversampling technique, and deep random forest. …”
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A Multicomponent Collaborative Fossil Fuel Power Plants Detection Framework Based on Geographic Analysis in Wide Areas by Ning Li, Min Jing, Wanxuan Geng, Shengkun Dongye, Hui Chen, Chen Ji, Liang Cheng

“…Next, we constructed a comprehensive FFPP dataset, including plants and their components, and trained two separate object detection models for FFPPs and their components. Subsequently, the FFPP model was used to perform coarse detection, followed by the refined detection of primary features (chimneys, square chimneys, and cooling towers) and auxiliary features (substations and storage tanks). …”
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CREDIT CARD FRAUD DETECTION USING LINEAR DISCRIMINANT ANALYSIS (LDA), RANDOM FOREST, AND BINARY LOGISTIC REGRESSION by Muhammad Ahsan, Tabita Yuni Susanto, Tiza Ayu Virania, Andi Indra Jaya

“…Therefore, pressuring them to continuously advance their fraud detection system is crucial. In this research, we describe fraud detection as a classification issue by comparing three methods. …”
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Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis by Christos Kokkotis, Kyriakos Apostolidis, Dimitrios Menychtas, Ioannis Kansizoglou, Evangeli Karampina, Maria Karageorgopoulou, Athanasios Gkrekidis, Serafeim Moustakidis, Evangelos Karakasis, Erasmia Giannakou, Maria Michalopoulou, Georgios Ch Sirakoulis, Nikolaos Aggelousis

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Medicare Fraud Detection Using Graph Analysis: A Comparative Study of Machine Learning and Graph Neural Networks by Yeeun Yoo, Jinho Shin, Sunghyon Kyeong

“…This study demonstrates that medicare fraud detection can be significantly enhanced by introducing graph analysis with considering the relationships among medical providers, beneficiaries, and physicians. …”
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Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning. by Himanshi Babbar, Shalli Rani, Maha Driss

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Detection of Malicious Office Open Documents (OOXML) Using Large Language Models: A Static Analysis Approach by Jonas Heß , Kalman Graffi

“…As a supplementary tool to contemporary antivirus software, it is currently able to assist in the analysis of malicious Microsoft Office documents by identifying and summarising potentially malicious indicators with a foundation in evidence, which may prove to be more effective with advancing technology and soon to surpass tailored machine learning algorithms, even without the utilisation of signatures and detection rules. …”
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