Early detection of fungal infection of Arabidopsis and brassica by Raman spectroscopy by Song-Yi Kuo, Ling-Ying Chiu, Ekta Jain, Gajendra Pratap Singh, Muhammad Nabil Syafiq Bin Jamaludin, Rajeev J. Ram, Rajeev J. Ram, Nam-Hai Chua, Nam-Hai Chua

“…Chitin, a recognized fungal pathogen-associated molecular pattern (PAMP), elicited a dose dependent positive Elicitor Response Index (ERI) in wild-type Arabidopsis. …”
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Developments in Deep Learning Artificial Neural Network Techniques for Medical Image Analysis and Interpretation by Olamilekan Shobayo, Reza Saatchi

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Unsupervised Fabric Defect Detection Based on Under-Complete Dictionary Reconstruction by LIU Jianxin, PAN Ruru, ZHOU Jian

“…To address the issue that most current automatic fabric defect detection methods still require manual selection of training sets and cannot achieve unsupervised learning, an automatic unsupervised defect detection method using the median robust extended local binary pattern (MRELBP) feature for flawless image screening and an under-complete dictionary reconstruction method for defect point detection are proposed. …”
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Application of soft computing techniques in machine reading of Quranic Kufic manuscripts by Aasim Zafar, Arshad Iqbal

“…The proposed system is based on word segmentation and employs a Histogram of Oriented Gradient (HOG) and Local Binary Pattern (LBP) feature extraction techniques. Later in the paper a comparison is given between the numerical results of proposed technique with previous Arabic text recognition techniques to show the effectiveness of present work. …”
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Determination of fracture mechanics parameters on a base of local displacement measurements by Yu. G. Matvienko, V.S. Pisarev, S. I. Eleonsky

“…Initial experimental information has a form of in-plane displacement component values, which are measured by electronic speckle-pattern interferometry at some specific points located near a crack tip. …”
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Exploring the performance of LBP-capsule networks with K-Means routing on complex images by Patrick Mensah Kwabena, Benjamin Asubam Weyori, Ayidzoe Abra Mighty

“…The original CapsNet uses CNNs as feature extractors, SoftMax for normalization, and dynamic routing (DR) to enable active capsules to make predictions resulting in the activation of higher-level capsules. …”
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Electronic Nose System Based on Metal Oxide Semiconductor Sensors for the Analysis of Volatile Organic Compounds in Exhaled Breath for the Discrimination of Liver Cirrhosis Patient... by Makhtar War, Benachir Bouchikhi, Omar Zaim, Naoual Lagdali, Fatima Zohra Ajana, Nezha El Bari

“…This study demonstrates the significant potential of e-nose technology towards VOCs analysis in exhaled breath, as a valuable tool for LC diagnosis. It also explores feature extraction methods and suitable algorithms for effectively distinguishing between LC patients and controls. …”
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MMG-Based Motion Segmentation and Recognition of Upper Limb Rehabilitation Using the YOLOv5s-SE by Gangsheng Cao, Shen Jia, Qing Wu, Chunming Xia

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Early real-time estimation of the basic reproduction number of emerging or reemerging infectious diseases in a community with heterogeneous contact pattern: Using data from Hong Ko... by Kin On Kwok, Bahman Davoudi, Steven Riley, Babak Pourbohloul

“…Based on this approach, we extend the existing methodology; the most recent method features intra- and inter-age groups contact heterogeneity. …”
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TENDENCIES OF CLIMATE CHANGES FOR THERMAL CONDITIONS IN THE COASTAL WATERS OF THE WESTERN BERING SEA AND ADJACENT AREAS IN THE LAST DECADES by I. D. Rostov, E. V. Dmitrieva, A. A. Vorontsov

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Filamentary Convolution for SLI: A Brain-Inspired Approach with High Efficiency by Boyuan Zhang, Xibang Yang, Tong Xie, Shuyuan Zhu, Bing Zeng

“…We propose filamentary convolution to replace rectangular kernels, reducing the parameters while preserving inter-frame features by focusing solely on frequency patterns. …”
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An Ensemble Approach for Detection of Malicious URLs Using SOM and Tabu Search Optimization by Simar Preet Singh, Abhilash Maroju, Mohammad Kamrul Hasan, Karan Tejpal

“…Enhanced methods that can handle large-scale datasets and identify new attack patterns are needed for the real-time identification of malicious URLs. …”
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An Efficient Fine-Grained Recognition Method Enhanced by Res2Net Based on Dynamic Sparse Attention by Qifeng Niu, Hui Wang, Feng Xu

“…The core approach leverages the inherent multi-scale representation power of Res2Net to capture discriminative patterns across different granularities. Crucially, the integrated Sparse Attention module operates dynamically, selectively amplifying the most informative features while attenuating irrelevant background noise and redundant details. …”
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Robust identification method of website fingerprinting against disturbance by ZHANG Jingxi, LI Tengyao, TU Yukuan, LUO Xiangyang

“…Subsequently, a hybrid feature matrix (HFM) was constructed to resist various defense disturbance by combining the features of both packet-level and session-level. …”
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Real time blood detection in CCTV surveillance using attention enhanced InceptionV3 by Adnan Khalil, Fakhre Alam, Dilawar Shah, Irshad khalil, Shujaat Ali, Muhammad Tahir

“…This study proposes a real-time deep learning framework that combines the InceptionV3 architecture with Convolutional Block Attention Modules to enhance spatial and channel-level feature discrimination. The model is further optimized through a proposed attention module that intensifies attention to small and minute blood-related patterns, even under challenging conditions such as occlusions, motion blur, and low visibility. …”
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Domain Knowledge Preservation in Financial Machine Learning: Evidence from Autocallable Note Pricing by Mohammed Ahnouch, Lotfi Elaachak, Erwan Le Saout

“…The component-wise analysis reveals complex interactions between autocall mechanisms and higher-order sensitivities, particularly affecting vanna and volga patterns near barrier levels. These findings provide empirical evidence that financial machine learning benefits from domain-specific feature engineering principles that preserve economic relationships. …”
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Predicting User Purchases From Clickstream Data: A Comparative Analysis of Clickstream Data Representations and Machine Learning Models by A. Aylin Tokuc, Tamer Dag

“…Notably, the hybrid representation with LightGBM achieved superior predictive performance, significantly outperforming alternative methods. Feature importance analysis revealed key factors influencing purchase likelihood, such as time since the last event, session duration, and product interactions. …”
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Efficient Sedimentary Facies Recognition Using Vision Transformer and Weakly Supervised Deep Multi-View Clustering by Hao Wu, Yu-Jie Dai, Xin-Yu Liu

“…First, we use ViT for feature extraction from sedimentary facies images, capturing global information through the self-attention mechanism, thereby enhancing the ability to recognize complex sedimentary facies patterns. …”
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Real defect partial discharge identification method for power cables joints based on integrated PJS-M and GA-SVM algorithm with multi-source fusion by Ling-Xuan Zhang, Yi-Yang Zhou, Shen-Jiong Yao, Jia-Luo Chai, Ying-Jing Chen, Zhou-Sheng Zhang

“…PD signals were collected using a combination of High-Frequency Current Transformer (HFCT) and Ultra High Frequency (UHF) sensors, capturing time-domain waveforms, frequency-domain spectra, and Phase-Resolved Partial Discharge (PRPD) patterns, from which feature quantities were extracted. …”
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Research on Multi-Step Prediction of Pipeline Corrosion Rate Based on Adaptive MTGNN Spatio-Temporal Correlation Analysis by Mingyang Sun, Shiwei Qin

“…Then, a dynamic adjacency matrix is adaptively learned to capture hidden spatial dependencies, while temporal convolution modules extract multi-scale temporal patterns, and the node sequences with integrated corrosion features are input into the adaptive MTGNN for prediction. …”
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