A Cloud Detection System for UAV Sense and Avoid: Analysis of a Monocular Approach in Simulation and Flight Tests by Adrian Dudek, Peter Stütz

“…The described workflow is based on parallelized detection, tracking and triangulation of features with prior segmentation of clouds in the image. …”
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A Robust and Efficient Machine Learning Framework for Enhancing Early Detection of Android Malware by Fandi Kurniawan, Deris Stiawan, Darius Antoni, Mohd Yazid Idris, Rahmat Budiarto

“…This study aims to develop a robust and efficient static analysis-based machine learning framework for early detection of Android malware. …”
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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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Interpretable Ordinal-Aware With Contrastive-Enhanced Anomaly Severity Detection on UAV Flight Log Messages by Swardiantara Silalahi, Tohari Ahmad, Hudan Studiawan, Eirini Anthi, Lowri Williams

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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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Estimation Of The Vocal Folds Vibration Fundamental Frequency by Higer Order Spectrum by Wiesław WSZOŁEK, Maciej KŁACZYŃSKI

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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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Modern Psychoactive Substances and Their Detection in Biomedical Samples by A. M. Grigoryev, V. N. Fateenkov

“…The purpose of the work is to review psychoactive compounds and methods of their detection performed for diagnostic purposes. The paper presents brief characteristics of the most common NPS, as well as features of their metabolism in the human. …”
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Unsupervised machine learning-based multi-attributes analysis for enhancing gas channel detection and facies classification in the serpent field, offshore Nile Delta, Egypt by Shaimaa A. El-Dabaa, Farouk I. Metwalli, Ali Maher, Amir Ismail

“…Abstract The prediction of highly heterogeneous reservoir parameters from seismic amplitude data is a major challenge. Seismic attribute analysis can enhance the tracking of subtle stratigraphic features. …”
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Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning by Jakub Horvath, Pavel Jedlicka, Marie Kratka, Zdenek Kubat, Eduard Kejnovsky, Matej Lexa

“…Our work shows the applicability of machine learning models to regulatory sequence analysis and classification, and demonstrates the important role of the identified motifs in LTR detection.…”
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Early Diabetic Retinopathy Detection from OCT Images Using Multifractal Analysis and Multi-Layer Perceptron Classification by Ahlem Aziz, Necmi Serkan Tezel, Seydi Kaçmaz, Youcef Attallah

“…<b>Methods:</b> This study introduces a novel framework for the early detection of DR through multifractal analysis of OCT images. …”
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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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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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Pathological and clinical insights into DICER1 hotspot mutated Sertoli-Leydig cell tumors: a comparative analysis by Zhuoyao Lyu, Yilin Liu, Jingci Chen, Pengyan Wang, Zhaohui Lu, Xiaoyan Chang, Xianlong Chen, Heng Ma, Shengwei Mo, Shuangni Yu, Jie Chen

“…Methods A retrospective analysis was conducted on 50 SLCTs. DICER1 RNase IIIb hotspot mutations were detected by the Sanger sequence. …”
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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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Lung Cancer Detection Utilizing Mixed Sensor Based Electronic Nose by Umit Ozsandikcioglu, Ayten Atasoy, Yusuf Sevim

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Toward a Recognition System for Mexican Sign Language: Arm Movement Detection by Gabriela Hilario-Acuapan, Keny Ordaz-Hernández, Mario Castelán, Ismael Lopez-Juarez

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