Deep Learning for Connectivity Identification in Random Subsurface Flows: A Methodological Workflow for Early Solute Arrival Time Quantification by A. Manzoni, F. P. J. deBarros, G. M. Porta, M. Riva, A. Guadagnini

“…Our methodology is based on a two‐stage approach that combines Convolutional Neural Networks (CNN) and Multi‐Layer Perceptron (MLP) techniques. …”
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Enhanced Mask R-CNN Incorporating CBAM and Soft-NMS for Identification and Monitoring of Offshore Aquaculture Areas by Jiajun Zhang, Yonggui Wang, Yaxin Zhang, Yanxin Zhao

“…In this study, a violation monitoring framework for marine aquaculture areas based on image recognition using an enhanced Mask R-CNN architecture incorporating a convolutional block attention module (CBAM) and soft non-maximum suppression (Soft-NMS) is proposed and applied in Sandu’ao. …”
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Needle detection and localisation for robot‐assisted subretinal injection using deep learning by Mingchuan Zhou, Xiangyu Guo, Matthias Grimm, Elias Lochner, Zhongliang Jiang, Abouzar Eslami, Juan Ye, Nassir Navab, Alois Knoll, Mohammad Ali Nasseri

“…Five convolutional neural networks with different architectures were evaluated. …”
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ECGConVT: A Hybrid CNN and Vision Transformer Model for Enhanced 12-Lead ECG Images Classification by Mudassar Khalid, Charnchai Pluempitiwiriyawej, Abdulkadhem A. Abdulkadhem, Imran Afzal, Tien Truong

“…We propose ECGConVT framework that combines Convolutional Neural Network (CNN) module for extracting local features, and Vision Transformer (ViT) module for capturing global features. …”
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Staged transfer learning for multi-label half-face emotion recognition by Mohamed M. Abd ElMaksoud, Sherif H. ElGohary, Ahmed H. Kandil

“…By combining this dataset with the established FER2013 dataset, we employ a staged transfer learning framework that effectively addresses the challenges of multi-label half facial emotion classification. …”
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Artificial intelligence derived grading of mustard gas induced corneal injury and opacity by Rajnish Kumar, Devansh M. Sinha, Nishant R. Sinha, Ratnakar Tripathi, Nathan Hesemann, Suneel Gupta, Anil Tiwari, Rajiv R. Mohan

“…The ResNet50-based model demonstrated the best performance, achieving 87% training accuracy, and 85% and 83% prediction accuracies on two independent test sets. This deep learning framework, combining Mask-RCNN with ResNet50 allows reliable and uniform grading of SM-induced corneal injury and opacity levels in affected eyes.…”
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Data-Driven Hybrid CNN-LSTM Neural Networks for Predicting Drying Kinetics of Green Tomatoes (Physalis ixocarpa) Integrating Mathematical Models by Carolina Livier Recio-Colmenares, Roxana Berenice Recio-Colmenares, Robin Fernando Conchas-Cedano, Isaac Pilatowsky-Figueroa, Cesar Alejandro Garcia Garcia

“…This hybrid CNN-LSTM model, coupled with the accurate mathematical models (especially the Two-Term Exponential), offers a robust framework for predicting and optimizing food dehydration.…”
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PoseAlign network for hybrid structure in 2D human pose estimation by Jin Zhang, Yabo Yin, Wenzhong Yang, Doudou Ren, Danny Chen

“…Therefore, we have combined the strengths of the ViTs framework and applied it to CNN-based HPE methods. …”
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Accurate Detection and Tracking of Small-Scale Vehicles in High-Altitude Unmanned Aerial Vehicle Bird-View Imagery by Heshan Zhang, Xin Tan, Mengwei Fan, Cunshu Pan, Zhanji Zheng, Shuang Luo, Jin Xu

“…This paper proposes a detection-based small-scale vehicle tracking framework that integrates an improved YOLOX network and the DeepSORT algorithm to address these issues. …”
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PlantCareNet: an advanced system to recognize plant diseases with dual-mode recommendations for prevention by Muhaiminul Islam, AKM Azad, Shifat E. Arman, Salem A. Alyami, Md Mehedi Hasan

“…The system utilizes a dual mode strategy that integrates advanced deep learning algorithms for precise disease diagnosis with a knowledge-based framework guided by experts for preventive measures. …”
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Assessment of economic well-being in South Africa based on remote sensing transfer learning by L. Wang, L. Wang, T. Long, T. Long, E. Adam

“…We take the established correlation between nighttime light intensity and economic activity and propose a framework to analyze it in parallel with environmental indicators derived from daytime satellite imagery. …”
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Dual Branch Encoding Feature Aggregation for Cloud and Cloud Shadow Detection of Remote Sensing Image by Naikang Shi, Haifeng Lin, Huiwen Ji, Min Xia

“…To tackle these challenges, this study introduces a dual-path neural network framework that synergistically combines convolutional neural networks (CNNs) and architectures. …”
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Interpretable capsule networks via self attention routing on spatially invariant feature surfaces by Peizhang Li, Jiyuan Ru, Qing Fei, Zhen Chen, Bo Wang

“…However, current classification approaches based on convolutional neural networks often suffer from limited generalization and robustness, particularly when processing data characterized by abstract class features and pronounced spatial attributes. …”
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MultiFG: integrating molecular fingerprints and graph embeddings via attention mechanisms for robust drug side effect prediction by Zuhai Hu, Jinxiang Yang, Linghao Ni, Liyuan Zhang, Bin Peng

“…We propose Multi Fingerprint and Graph Embedding model (MultiFG), a novel deep learning framework that integrates diverse molecular fingerprint types, graph-based embeddings, and similarity features of drug–side effect pairs. …”
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A Style Transfer Method for Chinese Landscape Painting Based on Detail Feature Extraction and Fusion by Jinghao HU, Guohua GENG, Meijun XIONG, Siyi LI, Yuhe ZHANG

“…This approach introduces the Swin–Transformer within the StyTr² network framework and uses the visual transformer to preserve the features of landscapes. …”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah, Seifeddine Bouallegue, Ridha Bouallegue

“…The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”
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Detection of Spark Erosion on Insulated Rail Joints by Deep Learning by Utku Kaya

“…The proposed methodology is based on a two-stage framework: in the first stage, the SqueezeNet convolutional neural network is used for the classification of rail images and the detection of IRJs. …”
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Thermal error modeling of slant bed CNC lathe spindle based on BiLSTM with data augmentation and grey wolf optimizer algorithm by Musab Alataiqeh, Hu Shi, Qiangqiang Qu, Xuesong Mei, Haitao Wang

“…This study establishes a comprehensive framework for predicting thermal errors in CNC machine tools, offering valuable insights for precision machining.…”
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Improved Visual SLAM Algorithm Based on Dynamic Scenes by Jinxing Niu, Ziqi Chen, Tao Zhang, Shiyu Zheng

“…Based on the classic framework of traditional visual SLAM, we propose a method that replaces the traditional feature extraction method with a convolutional neural network approach, aiming to enhance the accuracy of feature extraction and localization, as well as to improve the algorithm’s ability to capture and represent the characteristics of the entire scene. …”
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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

“…These pathways converge into a unified predictive framework designed to enhance the model’s accuracy. …”
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