Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction by Ali M. Hasan, Asaad F. Qasim, Hamid A. Jalab, Rabha W. Ibrahim

“…The obtained features are classified using a long short-term memory (LSTM) neural network classifier. …”
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A feasibility study of ballet education using measurement and analysis on partial features of still scenes by So-Hyun Park, Gwang-Soo Hong, Sun-Woo Park, Aziz Nasridinov, In-Ja Park, Byung-Kyu Kim, Young-Ho Park

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Social Network Supported Process Recommender System by Yanming Ye, Jianwei Yin, Yueshen Xu

“…This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. …”
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ALTERNATIVE FOOD NETWORKS E CITTÀ IN ITALIA by Filippo Randelli, Benedetto Rocchi, Stefania Giampaolo

“…Using a spatial analysis we will be able to evaluate which context characteristics foster the evolution of farmers direct sale. …”
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Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…Existing neural network architectures often struggle with two critical limitations: (1) information loss during dataset length standardization, where variable-length samples are forced into fixed dimensions, and (2) inefficient feature selection in single-modal systems, which treats all features equally regardless of relevance. …”
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Revisiting Information Cascades in Online Social Networks by Michael Sidorov, Ofer Hadar, Dan Vilenchik

“…In this study we aim to address this gap by proposing a method to predict the activity of individual users in an OSN, relying solely on their interactions rather than prior knowledge of their social network. We evaluated our results on four large datasets, each comprising over 14 million tweets, recorded on <b>X</b> social network across four different topics over several month. …”
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Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…Extensive experiments on synthetic and real-world social networks, including email and phone call networks, demonstrate the superior performance of our model in community detection and tracking temporal network evolution. …”
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Structural reinforcement-based graph convolutional networks by Jisheng Qin, Qianqian Wang, Tao Tao

“…Graph Convolutional Network (GCN) is a tool for feature extraction, learning, and inference on graph data, widely applied in numerous scenarios. …”
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Enhanced Skin Lesion Classification Using Deep Learning, Integrating with Sequential Data Analysis: A Multiclass Approach by Azmath Mubeen, Uma N. Dulhare

“…This study introduces a novel method for classifying skin lesions, including nodules, by combining a unified attention (UA) network with deep convolutional neural networks (DCNNs) for feature extraction. …”
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Regional differences and distributional dynamic evolution of science and technology innovation driven green development efficiency in Chinese agriculture by Lingling Wang, Min Li, Panpan Zhang

“…This study assesses the spatiotemporal efficiency of ASTI in promoting green agricultural development across 30 Chinese provinces, aiming to uncover persistent regional disparities and dynamic evolution patterns.MethodsConstructing an evaluation model and indicator system for science, technology and innovation driven green development in agriculture, applying the network Slack-Based Measure (SBM) model to measure the level of efficiency, and analyzing regional differences and dynamic features through the Theil index, kernel density estimation and spatial Markov methods.Results and discussionThis study explores the regional differences and distributional dynamic evolution of the efficiency of Agricultural science and technology innovation (ASTI) driven green development in China. …”
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Vehicle re-identification with multiple discriminative features based on non-local-attention block by Lu Bai, Leilei Rong

“…The key to solve this difficulty is to make full use of the multiple discriminative features of vehicles. Therefore, this paper proposes a multiple discriminative features extraction network (MDFE-Net) that can enhance the distance dependence on the vehicle’s multiple discriminative features by non-local attention, which in turn enhances the discriminative power of the network. …”
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Deep multimodal representations and classification of first-episode psychosis via live face processing by Rahul Singh, Rahul Singh, Rahul Singh, Yanlei Zhang, Dhananjay Bhaskar, Dhananjay Bhaskar, Vinod Srihari, Cenk Tek, Xian Zhang, Xian Zhang, J. Adam Noah, J. Adam Noah, Smita Krishnaswamy, Smita Krishnaswamy, Smita Krishnaswamy, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch

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A hybrid deep learning-based approach for optimal genotype by environment selection by Zahra Khalilzadeh, Motahareh Kashanian, Saeed Khaki, Lizhi Wang

“…Using a new yield dataset containing 93,028 records of soybean hybrids across 159 locations, 28 states, and 13 years, with 5,838 distinct genotypes and daily weather data over a 214-day growing season, we developed two convolutional neural network (CNN) models: one that integrates CNN and fully-connected neural networks (CNN model), and another that incorporates a long short-term memory (LSTM) layer after the CNN component (CNN-LSTM model). …”
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Integrating SAM priors with U-Net for enhanced multiclass cell detection in digital pathology by Zheng Wu, Ji-Yun Yang, Chang-Bao Yan, Cheng-Gui Zhang, Hai-Chao Yang

“…While classic segmentation networks like U-Net have gained widespread adoption in medical imaging, their integration with external prior features remains limited, thereby restricting the potential enhancement of segmentation accuracy. …”
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Prediction of Remaining Useful Life of Operating Mechanism Driven by Deep Feature in Classification Model by Xilei Dong, Fuping Zhang, Yunyang Ye, Huan Zhang

“…Accurate evaluation of the remaining service life of the operating mechanism plays an important role in ensuring the reliable operation of power transmission and distribution network. …”
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Cloud-Based Intrusion Detection Approach Using Machine Learning Techniques by Hanaa Attou, Azidine Guezzaz, Said Benkirane, Mourade Azrour, Yousef Farhaoui

“…Cloud computing (CC) is a novel technology that has made it easier to access network and computer resources on demand such as storage and data management services. …”
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Explainable AI Meets Synthetic Data: A Deep Learning Framework for Detecting Network Intrusion in NextG Network Infrastructure by Md Junayed Hossain, Khorshed Alam, Md Fahad Monir, Md Mozammal Hoque, Tarem Ahmed

“…The CNN and LSTM models, applied independently, leverage their respective strengths to extract spatial and temporal features from network traffic, achieving robust classification accuracy. …”
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THz image recognition of moldy wheat based on multi-scale context and feature pyramid by Yuying Jiang, Yuying Jiang, Yuying Jiang, Xinyu Chen, Xinyu Chen, Xinyu Chen, Hongyi Ge, Hongyi Ge, Hongyi Ge, Xixi Wen, Xixi Wen, Xixi Wen, Mengdie Jiang, Mengdie Jiang, Mengdie Jiang, Yuan Zhang, Yuan Zhang, Yuan Zhang

“…Firstly, the network uses the residual network ResNeXt as the baseline network, and incorporates a multi-scale contextual feature extraction module, which is more helpful to determine the important discriminative regions in the whole image to extract more image detail features. …”
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Open Source Evaluatology: An evaluation framework and methodology for open source ecosystems based on evaluatology by Fanyu Han, Shengyu Zhao, Wei Wang, Aoying Zhou, Weining Qian, Xuan Zhou, Jiaheng Peng, Lan You, Yang Chen, Xiaoya Xia, Yenan Tang, Liyun Yang, Chunqi Tian

“…A combined evaluation model (EM) based on statistical metrics and network metrics is also introduced; (3) Experimental validation using the GitHub dataset shows that the proposed evaluation framework effectively assesses various features of open-source projects, developers, and communities, and has been verified in multiple practical application scenarios. …”
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Neutrophil Gelatinase-Associated Lipocalin Levels in Early and Late Onset Preeclampsia by Onur Guralp, Nevin Tuten, Mahmut Oncul, Serdar A Acikgoz, Hakan Ekmekci, Abdullah Tuten

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