MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation by Muna Khalaf, Ban N. Dhannoon

“…This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. …”
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Mobile Apps to Prevent Violence Against Women and Girls (VAWG): Systematic App Research and Content Analysis by Md Hafizur Rahman, Nasimul Ghani Usmani, Pradip Chandra, Ridwana Maher Manna, Anisuddin Ahmed, Mohammad Sohel Shomik, Shams El Arifeen, Aniqa Tasnim Hossain, Ahmed Ehsanur Rahman

“…ObjectiveTherefore, we aimed to systematically evaluate the trends, geographical distribution, functional categories, available features, and feature evolution of mobile apps designed to prevent violence against women and girls (VAWG). …”
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Bridging Explainability and Security: An XAI-Enhanced Hybrid Deep Learning Framework for IoT Device Identification and Attack Detection by Prabhav Jain, Anshika Rathour, Aashima Sharma, Gurpal Singh Chhabra

“…We evaluated the proposed system using the CIC IoT2024-DIAD dataset, which includes traffic data from seven device classes and 25 network features. …”
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Transformers for Neuroimage Segmentation: Scoping Review by Maya Iratni, Amira Abdullah, Mariam Aldhaheri, Omar Elharrouss, Alaa Abd-alrazaq, Zahiriddin Rustamov, Nazar Zaki, Rafat Damseh

“…The most frequent evaluation metric was the Dice score (n=63, 94.03%). …”
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Prediction of Highway Tunnel Pavement Performance Based on Digital Twin and Multiple Time Series Stacking by Gang Yu, Shuang Zhang, Min Hu, Y. Ken Wang

“…This paper (1) establishes an MTSS prediction model with heterogeneous stacking of eXtreme gradient boosting (XGBoost), the artificial neural network (ANN), random forest (RF), ridge regression, and support vector regression (SVR) component learners after exploratory data analysis (EDA); (2) proposes a method based on multiple time series feature extraction to accurately predict the pavement performance change trend, using the highway segment as the minimum computing unit and considering multiple factors; (3) uses grid search with the k-fold cross validation method to optimize hyperparameters to ensure the robustness, stability, and generalization ability of the prediction model; and (4) constructs a digital twin for pavement performance prediction to realize the real-time dynamic evolution of prediction. …”
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Ensemble-RNN: A Robust Framework for DDoS Detection in Cloud Environment by Asha Varma Songa, Ganesh Redy Karri

“…These selected features are then used to classify the network traffic as either normal or attack, employing RNN. …”
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MWG-UNet++: Hybrid Transformer U-Net Model for Brain Tumor Segmentation in MRI Scans by Yu Lyu, Xiaolin Tian

“…The proposed model called Residual Attention U-shaped Network (RAUNet) for brain tumor segmentation leverages the robust feature extraction capabilities of U-Net and the global context awareness provided by transformers to improve segmentation accuracy. …”
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Analysis for Detecting Banana Leaf Disease Using the CNN Method by Nita Helmawati, Ema Utami

“…The dataset was divided into 70% for training, 20% for validation, and 10% for testing, to ensure robust model evaluation. The CNN model was trained to recognize important visual features on banana leaves that indicate disease infection. …”
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Using Graph-Based Maximum Independent Sets with Large Language Models for Extractive Text Summarization by Cengiz Hark

“…Experiments on the Document Understanding Conference (DUC) and Cable News Network (CNN)/DailyMail datasets are conducted with different summary lengths to evaluate the performance of the framework. …”
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Improvement of RT-DETR model for ground glass pulmonary nodule detection. by Siyuan Tang, Qiangqiang Bao, Qingyu Ji, Tong Wang, Naiyu Wang, Min Yang, Yu Gu, Jinliang Zhao, Yuhan Qu, Siriguleng Wang

“…This article proposed an algorithm based on RT-DETR model with the following enhancement: 1) optimize the backbone network with FCGE blocks to increase the detection accuracy of small-sized and blurred edge nodules; 2) replace the AIFI module with HiLo-AIFI module to reduce redundant computation and improve the detection accuracy of pure ground glass pulmonary nodules and mixed ground glass pulmonary nodules; 3) replace the DGAK module with CCFF module to address the issue of capturing complex features and recognition of irregularly shaped ground glass nodules. …”
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Toward general object search in open reality by Gang Shen, Wenjun Ma, Guangyao Chen, Yonghong Tian

“…To address these issues, we formalize the GOSO problem and propose a simple yet effective architecture named Siamese Exchanged Attention Network (SEA-Net). Specifically, based on a standard siamese structure, SEA-Net introduces a novel branch that comprises multiple stage-stacked Siamese Exchanged Attention (SEA) layers followed by a Hierarchical Feature Fusion (HFF) module, enabling efficient scale adaptation and the extraction of matching-friendly deep features. …”
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Survey of research on encrypted traffic classification based on machine learning by FU Yu, LIU Taotao, WANG Kun, YU Yihan

“…The content was further subdivided into seven stages: traffic collection, dataset construction, data preprocessing, feature extraction, feature selection, classification models, and performance evaluation. …”
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DMoVGPE: predicting gut microbial associated metabolites profiles with deep mixture of variational Gaussian Process experts by Qinghui Weng, Mingyi Hu, Guohao Peng, Jinlin Zhu

“…During training, the gating network refines expert selection, dynamically adjusting their contribution based on the input features. …”
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BTFBS: Binding Prediction of Bacterial Transcription Factors and Binding Sites Based on Deep Learning by Bingbing Jin, Song Liang, Xiaoqian Liu, Rui Zhang, Yun Zhu, Yuanyuan Chen, Guangjin Liu, Tao Yang

“…The model takes both the amino acid sequences of bacterial transcription factors and the nucleotide sequences of binding sites as inputs, and extracts features through convolutional neural network and MultiheadAttention. …”
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Automation of aeronautical information processing based on multi-agent technologies by D. E. Eshmuradov, T. D. Elmuradov, N. M. Turayeva

“…In the research process, a formal definition of the multi-agent system of automatic aeronautical information processing is presented, which involves a set of agents, environment of agent functioning, a set of permissible relations between agents, description of rules for forming a network of agents, a set of individual and joint actions, communication interactions, behavior and actions strategies, a possibility of system evolution. …”
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Multi-mode geometrically gated encryption with 4D morphing hydrogel by Xin Wen, Kaihang Zhang, Baoyi Wu, Guancong Chen, Ning Zheng, Jingjun Wu, Xuxu Yang, Tao Xie, Qian Zhao

“…Consequently, the corresponding optical information can be gated based on these geometric features, thereby decrypting the correct permutation of information. …”
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Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

“…First, we applied preprocessing, Term Frequency-Inverse Document Frequency feature extraction methods, and then applied classification algorithms. …”
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Advances in hydrogel research: a 25-year bibliometric overview by Dongbin Zhang, Mengru Qiu, Yu Tian, Shuo Zhang, Fan Wu

“…Abstract This study presents a comprehensive bibliometric analysis of hydrogel research from 2000 to 2025, examining 101,291 publications from the OpenAlex database to highlight the field’s evolution, trends, and impact, providing a better landscape of the field. …”
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Fuzzy model-based analysis of user feedback for product development insights by Anna Sudár, Borbála Berki, Ildikó Horváth

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Community Detection Framework Using Deep Learning in Social Media Analysis by Ao Shen, Kam-Pui Chow

“…Our main idea is to utilize social network topology and social network communication content to construct user features. …”
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