Mining behavior pattern of mobile malware with convolutional neural network by Xin ZHANG, Weizhong QIANG, Yueming WU, Deqing ZOU, Hai JIN

“…The features extracted by existing malicious Android application detection methods are redundant and too abstract to reflect the behavior patterns of malicious applications in high-level semantics.In order to solve this problem,an interpretable detection method was proposed.Suspicious system call combinations clustering by social network analysis was converted to a single channel image.Convolution neural network was applied to classify Android application.The model trained was used to find the most suspicious system call combinations by convolution layer gradient weight classification activation mapping algorithm,thus mining and understanding malicious application behavior.The experimental results show that the method can correctly discover the behavior patterns of malicious applications on the basis of efficient detection.…”
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DART-Vetter: A Deep Learning Tool for Automatic Triage of Exoplanet Candidates by Stefano Fiscale, Laura Inno, Alessandra Rotundi, Angelo Ciaramella, Alessio Ferone, Christian Magliano, Luca Cacciapuoti, Veselin Kostov, Elisa V. Quintana, Giovanni Covone, Maria Teresa Muscari Tomajoli, Vito Saggese, Luca Tonietti, Antonio Vanzanella, Vincenzo Della Corte

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Tunnel Crack Segmentation Algorithm Based on Feature Enhancement by Lihua Feng, Aijun Yao, An Huang

“…To address these challenges, this paper proposes a tunnel crack detection method. Firstly, a novel Dynamic Feature Enhancement Network (DFEN) module is designed to extract preliminary features using a feature extractor and selectively enhance feature representations through a gating mechanism. …”
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Advancing mango quality assurance: Non‐destructive detection of spongy tissue using visible near‐infrared spectroscopy and machine learning classification by Patil Rajvardhan Kiran, Md Yeasin, Pramod Aradwad, T. V. Arunkumar, Roaf Ahmad Parray

“…Through preprocessing and principal component analysis of spectral reflectance data for feature extraction and wavelength optimization, successful wavelength ranges of 650–970 nm were identified, effectively distinguishing between healthy and damaged mangoes. …”
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OCRClassifier: integrating statistical control chart into machine learning framework for better detecting open chromatin regions by Xin Lai, Xin Lai, Min Liu, Yuqian Liu, Xiaoyan Zhu, Jiayin Wang, Jiayin Wang

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Motion velocity as a preattentive feature in cartographic symbolization by Paweł Cybulski, Vassilios Krassanakis

“…The same applied to symbols’ shape. Eye movement analysis revealed that successful detection was closely related to the fixation on the target after initial preattentive vision. …”
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Analysis of electroencephalography oscillation characteristics in spinal cord injury patients with neuropathic pain by Dezheng Wang, Xinting Zhang, Shouwei Yue, Dongju Guo, Lei Jiang, Chao Feng, Jiancai Leng, Shaolei Huang, Yang Zhang, Fangzhou Xu

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Interpretable multitask deep learning model for detecting and analyzing severity of rice bacterial leaf blight by Sudhesh K. M, Aarthi R., Sainamole Kurian. P, Sikha O.K

“…The Convolutional Block Attention Module (CBAM) is independently applied to both the RGB image and its corresponding segmentation mask to emphasize important visual and spatial features. Enhanced features are fused and fed into a lightweight MobileNetV2 classifier for disease severity prediction. …”
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Elevation Data Statistical Analysis and Maximum Likelihood Estimation-Based Vehicle Type Classification for 4D Millimeter-Wave Radar by Mengyuan Jing, Haiqing Liu, Fuyang Guo, Xiaolong Gong

“…The elevation data collected by 4D radar from a real road scenario are applied for further analysis. By establishing radar coordinate systems and geodetic coordinate systems, the distribution feature of vehicles’ elevation is analyzed by spatial geometric transformation referring to the radar installation parameters, and a Gaussian-based probability distribution model is subsequently proposed. …”
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Early detection of thermal image based T1 breast cancer using enhanced multiwavelet denoised convolution neural network with region based analysis by P. Geetha, S. UmaMaheswari

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Design and Analysis of a Sowing Depth Detection and Control Device for a Wheat Row Planter Based on Fuzzy PID and Multi-Sensor Fusion by Yueyue Li, Bing Qi, Encai Bao, Zhong Tang, Yi Lian, Meiyan Sun

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Mango (Mangifera indica) tree detection and counting in mango orchard with satellite images using deep learning model YOLO: A comparative analysis by LALIT BIRLA, ANSHU BHARADWAJ, RAJNI JAIN, CHANDAN KUMAR DEB, VINAY KUMAR SEHGAL, RAMASUBRAMANIAN V

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Interdisciplinary framework for cyber-attacks and anomaly detection in industrial control systems using deep learning by Qawsar Gulzar, Khurram Mustafa

“…We employed Sparse Principal Component Analysis (SPCA) to extract higher-order features. We conducted experiments on the three datasets: the Secure Water Treatment System (SWaT), the Water Distribution (WADI), and the Gas Heating Loop (GHL). …”
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Plot-scale peanut yield estimation using a phenotyping robot and transformer-based image analysis by Zhengkun Li, Rui Xu, Nino Brown, Barry L. Tillman, Changying Li

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LLM-MalDetect: A Large Language Model-Based Method for Android Malware Detection by Ruirui Feng, Hui Chen, Shuo Wang, Md Monjurul Karim, Qingshan Jiang

“…To address this gap, we introduce LLM-MalDetect, a novel framework that improves LLM-based APK analysis by explicitly modeling semantic dependencies and leveraging structured prompt engineering for optimized detection. …”
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Wind energy system fault classification and detection using deep convolutional neural network and particle swarm optimization‐extreme gradient boosting by Chun‐Yao Lee, Edu Daryl C. Maceren

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A Comparative Study of Two-Stage Intrusion Detection Using Modern Machine Learning Approaches on the CSE-CIC-IDS2018 Dataset by Isuru Udayangani Hewapathirana

“…This study proposes a novel two-stage intrusion detection framework using the CSE-CIC-IDS2018 dataset, a comprehensive and realistic benchmark for network traffic analysis. …”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…Subsequently, the extracted features were subjected to iterative neighborhood component analysis (INCA) for feature selection, after which they were classified using the k-nearest neighbor (kNN) algorithm. …”
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Machine Learning-Based Detection of Archeological Sites Using Satellite and Meteorological Data: A Case Study of Funnel Beaker Culture Tombs in Poland by Krystian Kozioł, Natalia Borowiec, Urszula Marmol, Mateusz Rzeszutek, Celso Augusto Guimarães Santos, Jerzy Czerniec

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Features of occult hepatitis B diagnostics in cancer patients by E. A. Shevyakova, T. A. Zykova, L. A. Velikorodnaya, A. V. Shaposhnikov

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