Automated Detection of Connective Tissue by Tissue Counter Analysis and Classification and Regression Trees by Josef Smolle, Peter Kahofer

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Static Analysis-based Detection of Android Malware using Machine Learning Algorithms by Omar Emad Saied, Karam Hatim Thanoon

“…The rapid growth of Android applications has led to increased security threats, making malware detection a critical concern in cybersecurity. This research proposes a static analysis-based technique that employs machine learning for Android malware detection. …”
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Morphological features of immune inflammation in patients with persistent post-traumatic uveitis by G. P. Zakharova, I. A. Filatova, V. O. Denisyuk

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Multilingual Sarcasm Detection for Enhancing Sentiment Analysis using Deep Learning Algorithms by Ahmed Derbala Yacoub, Amal Elsayed Aboutabl, Salwa O. Slim

“…This research explores how sentiment analysis (SA) and sarcasm detection (SD) intersect, highlighting challenges in identifying how sarcasm influences sentiment polarity. …”
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Audio–Visual Synchronization and Lip Movement Analysis for Real-Time Deepfake Detection by Muhammad Javed, Zhaohui Zhang, Fida Hussain Dahri, Asif Ali Laghari, Martin Krajčík, Ahmad Almadhor

“…To address this issue, we propose a novel Audio–Visual Synchronisation and Fusion Framework (AVSFF) for real-time detection of deepfakes. This approach focuses on fine-grained lip movement analysis by detecting subtle inconsistencies between lip movements and corresponding audio. …”
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Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…This research focuses on detecting Bot-IoT activity using the Bot-IoT UNSW Canberra 2018 dataset. …”
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Tongue Color Analysis and Diseases Detection Based on a Computer Vision System by Abdulghafor Khudhaer Abdullah, Saleem Lateef Mohammed, Ali Al-Naji, Mohammed Sameer Alsabah

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Wavelet-Based Analysis of Motor Current Signals for Detecting Obstacles in Train Doors by Yaojung Shiao, Premkumar Gadde, Chun-Yu Liu

“…The norm and peak of the current are used as obstacle detection features, and appropriate threshold values are obtained from a simulation. …”
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Video-Based Detection Infrastructure Enhancement for Automated Ship Recognition and Behavior Analysis by Xinqiang Chen, Lei Qi, Yongsheng Yang, Qiang Luo, Octavian Postolache, Jinjun Tang, Huafeng Wu

“…Ship behavior analysis, one of the fundamental tasks for fulfilling smart video-based detection infrastructure, has become an active topic in the CAS community. …”
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A Disentangled Representation-Based Multimodal Fusion Framework Integrating Pathomics and Radiomics for KRAS Mutation Detection in Colorectal Cancer by Zhilong Lv, Rui Yan, Yuexiao Lin, Lin Gao, Fa Zhang, Ying Wang

“…In this paper, we propose a Disentangled Representation-based Multimodal Fusion framework integrating Pathomics and Radiomics (DRMF-PaRa) for KRAS mutation detection. Specifically, the DRMF-PaRa model consists of three parts: (1) the pathomics learning module, which introduces a tissue-guided Transformer model to extract more comprehensive and targeted pathological features; (2) the radiomics learning module, which captures the generic hand-crafted radiomics features and the task-specific deep radiomics features; (3) the disentangled representation-based multimodal fusion module, which learns factorized subspaces for each modality and provides a holistic view of the two heterogeneous phenotypic features. …”
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Hardware Trojans detection based on projection pursuit by Peng ZHANG, Xin-cheng WANG, Qing ZHOU

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Zipper Pattern: An Investigation into Psychotic Criminal Detection Using EEG Signals by Gulay Tasci, Prabal Datta Barua, Dahiru Tanko, Tugce Keles, Suat Tas, Ilknur Sercek, Suheda Kaya, Kubra Yildirim, Yunus Talu, Burak Tasci, Filiz Ozsoy, Nida Gonen, Irem Tasci, Sengul Dogan, Turker Tuncer

“…In the feature selection phase of the proposed XFE model, an iterative neighborhood component analysis (INCA) feature selector was used to choose the most distinctive features. …”
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Capturing Fine-Grained Food Image Features Through Iterative Clustering and Attention Mechanisms by Wei He, Mengmeng Liu, Qingqi Liang

“…Food image recognition is a crucial initial step for food detection, nutritional analysis, and dietary recommendations. …”
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Detecting and Classifying Android Malware Using Static Analysis along with Creator Information by Hyunjae Kang, Jae-wook Jang, Aziz Mohaisen, Huy Kang Kim

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Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis by Zishen Zhang, Hong Cheng, Meiyu Chen, Lixin Zhang, Yudou Cheng, Wenjuan Geng, Junfeng Guan

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Enhancing Disease Detection in the Aquaculture Sector Using Convolutional Neural Networks Analysis by Hayin Tamut, Robin Ghosh, Kamal Gosh, Md Abdus Salam Siddique

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Automated Anomaly Detection and Causal Analysis for Civil Aviation Using QAR Data by Xin Dang, Congcong Hua, Chuitian Rong

“…The proposed method can monitor multiple events in one routine and provide a causal analysis. In the causal analysis process, the Shapley additive interpretation method is applied to produce analysis report for detected anomalies. …”
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Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis by Mohammad Hasan, Mohammad Shahriar Rahman, Helge Janicke, Iqbal H. Sarker

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Detection of Hepatocellular Carcinoma Using Optimized miRNA Combinations and Interpretable Machine Learning Models by Zhengwu Long, Lisheng Zhang

“…Both permutation feature importance and SHAP analysis identified hsa-miR-93 and hsa-miR-139 as key miRNAs for HCC prediction. …”
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A Full-Scale Shadow Detection Network Based on Multiple Attention Mechanisms for Remote-Sensing Images by Lei Zhang, Qing Zhang, Yu Wu, Yanfeng Zhang, Shan Xiang, Donghai Xie, Zeyu Wang

“…Shadows degrade image quality and complicate interpretation, underscoring the importance of accurate shadow detection for many image analysis tasks. However, due to the complex backgrounds and variable shadow characteristics of remote sensing images (RSIs), existing methods often struggle with accurately detecting shadows of various scales and misclassifying dark, non-shaded areas as shadows. …”
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