A Multi-Scale Interpretability-Based PET-CT Tumor Segmentation Method by Dangui Yang, Yetong Wang, Yimeng Ma, Houqun Yang

“…Finally, visualization and perturbation experiments further validate the effectiveness of our method in emphasizing critical features.…”
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DEEP LEARNING-BASED SUPER-RESOLUTION TECHNIQUES: A COMPARATIVE ANALYSIS WITH RECENT INSIGHTS by Renuka Sambhaji Sindge, Maitreyee Dutta, Jagriti Saini

“…Afterwards, this paper discussed a group of standard frameworks and benchmark datasets with relevant features, performance evaluation metrics, and real-world applications to facilitate improved user experiences, analysis, and decision-making and open issues concerning single and multiple SR. …”
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Islanding Detection Methods and Challenges for Distribution Generation: A Technological Review by Farshad Aslani, Shuhui Li

“…Islanding detection poses a significant technical challenge for the reliable operation of grid-connected photovoltaic (PV) systems, particularly as the deployment of distributed generation (DG) increases across modern power networks. An undetected islanding event may jeopardize the safety of utility personnel, degrade power quality, cause voltage and frequency instability, and lead to malfunction or damage of sensitive electrical equipment. …”
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Leveraging Perspective Transformation for Enhanced Pothole Detection in Autonomous Vehicles by Abdalmalek Abu-raddaha, Zaid A. El-Shair, Samir Rawashdeh

“…Perspective transformation improves the visibility and clarity of potholes by virtually bringing them closer and enlarging their features, which is particularly beneficial given the fixed-size input requirement of object detection networks, typically significantly smaller than the raw image resolutions captured by cameras. …”
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Morphological characteristics and controlling factors of the piedmont fan systems in the Zanskar region, Northwest Himalaya, India by Mohammad Irfan, Bikram Singh Bali, Ahsan Afzal

“…Piedmont fans are prominent geomorphic features formed at the transition between mountain slopes and valley floors. …”
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Early diagnosis of autism across developmental stages through scalable and interpretable ensemble model by Nasirul Mumenin, Maisha Mumtaz Rahman, Mohammad Abu Yousuf, Farzan M. Noori, Md Zia Uddin

“…The proposed framework leverages a stacked ensemble model, combining Random Forest (RF), Extra Tree (ET), and CatBoost (CB) as base classifiers, with an Artificial Neural Network (ANN) serving as the meta-classifier. The methodology addresses class imbalance using Safe-Level SMOTE, dimensionality reduction via Principal Component Analysis (PCA), and feature selection using Mutual Information and Pearson correlation. …”
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Hybrid boosted attention-based LightGBM framework for enhanced credit risk assessment in digital finance by Chengwei Ying, Anlu Shi, Xiongyi Li

“…The HBA-LGBM model introduces four key innovations: (1) a multi-stage feature selection mechanism that dynamically filters key borrower attributes; (2) an attention-based feature enhancement layer, which prioritizes critical financial risk factors dynamically based on contextual importance; (3) a hybrid boosting strategy, integrating LightGBM with an adaptive neural network, enabling the model to capture complex borrower behavior and non-linear credit risk patterns; and (4) an advanced imbalanced learning strategy, combining synthetic data augmentation and cost-sensitive learning to mitigate class imbalance and enhance minority class predictions. …”
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Advancing precision agriculture: A comparative analysis of YOLOv8 for multi-class weed detection in cotton cultivation by Ameer Tamoor Khan, Signe Marie Jensen, Abdul Rehman Khan

“…The enhanced architecture of YOLOv8, featuring anchor-free detection, an advanced Feature Pyramid Network (FPN), and an optimized loss function, enables accurate detection even under challenging conditions. …”
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A Hybrid Dropout Method for High-Precision Seafloor Topography Reconstruction and Uncertainty Quantification by Xinye Cui, Houpu Li, Yanting Yu, Shaofeng Bian, Guojun Zhai

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Exploring the effect of training set size and number of categories on ice crystal classification through a contrastive semi-supervised learning algorithm by Y. Chu, Y. Chu, H. Zhang, X. Li, J. Henneberger

“…The algorithm consists of an upstream unsupervised learning network tasked with extracting meaningful representations from a large number of unlabeled ice crystal images, and a downstream supervised network is fine-tuned with a small subset of labeled images of the entire dataset to perform the classification task. …”
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The intellectual paradigm and scientific mapping of brand image in International Researches by Maryam Najafi Yazdi, Seyed Hassan Hataminasab, Shahnaz Nayebzadeh

“…After searching, screening, and qualitative evaluation; the final analysis has been done on 521 articles. …”
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Prediction of the risk of transplant rejection based on RNA sequencing data of PBMCs before transplantation by Yu Gong, Yuan Wang, Kazuyoshi Takeda, Saori Hirota, Yui Maehara, Ko Okumura, Koichiro Uchida

“…Here, we applied a transcriptomics database of recipients’ peripheral blood mononuclear cells (PBMCs) before liver or kidney transplantation on the weighted gene co-expression network and machine learning models to evaluate the risk of rejection. …”
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Effective Customization of Evolutionary Algorithm-Based Energy Management System Optimization for Improved Battery Management in Microgrids by Alessandro Niccolai, Silvia Trimarchi, Lisa Francesca Barbazza, Alessandro Gandelli, Riccardo Zich, Francesco Grimaccia, Sonia Leva

“…The proposed system is highly flexible, making it applicable to different network architectures and various objective functions. …”
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New Model for Weather Stations Integrated to Intelligent Meteorological Forecasts in Brasilia by Thomas Alexandre da Silva, Andre L. M. Serrano, Erick R. C. Figueiredo, Geraldo P. Rocha Filho, Fábio L. L. de Mendonça, Rodolfo I. Meneguette, Vinícius P. Gonçalves

“…Powered by photovoltaic panels and batteries, it operates uninterruptedly under variable weather conditions, with data collected being sent via WiFi to a Web API that adapts the MZDN-HF (Meteorological Zone Delimited Neural Network–Hourly Forecaster) model compilation for Brasilia to produce accurate 24 h multivariate forecasts, which were evaluated through MAE, RMSE, and R² metrics. …”
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Toward the Reconstruction of Substorm‐Related Dynamical Pattern of the Radiowave Auroral Absorption by V. A. Sergeev, M. A. Shukhtina, N. A. Stepanov, D. D. Rogov, A. V. Nikolaev, E. Spanswick, E. Donovan, T. Raita, A. Kero

“…Using global riometer network we test the method performance for stations in the middle of auroral zone (at corrected geomagnetic latitudes of 65–67°) where generally the absorption amplitude is largest. …”
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Structural Damage Detection in the Wooden Bridge Using the Fourier Decomposition, Time Series Modeling and Machine Learning Methods by Younes Nouri, Farzad Shahabian, Hashem Shariatmadar, Alireza Entezami

“…The algorithms are utilized consist of Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), support vector machines (SVM), ensemble learning, and decision tree. …”
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SH-SDS: a new static-dynamic strategy for substation host security detection by Yang Diao, Hui Chen, Wei Liu, Abdur Rasool

“…This article proposes a new static-dynamic strategy for host security detection by implementing a system prototype and evaluating its detection accuracy. To reduce the subjectivity in manually selecting features, we combine classified protection for cybersecurity-related standards and construct the requirement generation algorithm to construct a network security detection standard library for the substation host. …”
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Peripheral blood immune cells from individuals with Parkinson's disease or inflammatory bowel disease share deficits in iron storage and transport that are modulated by non-steroid... by MacKenzie L. Bolen, Beatriz Nuñes Gomes, Blake Gill, Kelly B. Menees, Hannah Staley, Janna Jernigan, Nikolaus R. McFarland, Ellen M. Zimmermann, Christopher E. Forsmark, Malú Gámez Tansey

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Adaptive Circular Receptive Field for Remote Sensing Image Target Detection by Ning Wen, Yun Ge, Xiaoyu Yang, Meigen Yu, Ting Wang

“…The Adaptive Circular Receptive Field Network (ACRFNet) is proposed to address these problems. …”
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Deep learning for enhancing automatic classification of M-PSK and M-QAM waveform signals dedicated to single-relay cooperative MIMO 5G systems by Haithem Ben Chikha, Alaa Alaerjan, Randa Jabeur

“…The proposed method leverages a convolutional neural network (CNN) classifier trained on a reduced set of discriminative features, including higher-order statistics and the differential nonlinear phase peak factor, which are extracted from the received signal. …”
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