An Ontology-Based Framework for Complex Urban Object Recognition through Integrating Visual Features and Interpretable Semantics by Xiao Xie, Xiran Zhou, Jingzhong Li, Weijiang Dai

“…In this paper, we present an ontology-based methodology framework for enabling object recognition through rules extracted from the high-level semantics, rather than unexplainable features extracted from a CNN. …”
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A Novel AI-Based Integrated Cybersecurity Risk Assessment Framework and Resilience of National Critical Infrastructure by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Sardar Sadaqat Ali

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A Novel Transformer-Based Multiscale Siamese Framework for High-Resolution Remote Sensing Change Detection by Liangjun Wang, Weitao Chen, Haoyi Wang, Zhengchao Chen

“…Change detection (CD) in remote sensing based on deep convolutional neural networks and transformers has played a crucial role in surface monitoring and resource development. …”
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Deep learning-based dual optimization framework for accurate thyroid disease diagnosis using CNN architectures by Zeeshan Ali Haider, Nasser A Alsadhan, Fida Muhammad Khan, Waleed Al-Azzawi, Inam Ullah Khan, Inam Ullah

“…This study introduces a novel deep learning framework utilizing advanced Convolutional Neural Networks (CNNs), specifically modified ResNet and InceptionV3 architectures, to improve the accuracy and efficiency of thyroid disease diagnosis. …”
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Knowledge Improved Hybrid DNN–KAN Framework for Intrusion Detection in Wireless Sensor Networks by M. Sriraghavendra, Muna Elsadig, Ines Hilali Jaghdam, S. Abdel-Khalek, B. Galeebathullah, Salem Alkhalaf

“…The proposed framework preprocesses and merges multiple datasets (WSN, NSL-KDD, and CICIDS2017), extracts features using Principal Component Analysis (PCA), and constructs a knowledge graph to embed expert-defined rules via Graph Convolutional Networks (GCNs). …”
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Spatiotemporal Forecasting of Solar and Wind Energy Production: A Robust Deep Learning Model with Attention Framework by Md. Shadman Abid, Razzaqul Ahshan, Mohammed Al-Abri, Rashid Al Abri

“…In this context, a novel robust deep learning model, termed the Convolutional Neural Network-Bidirectional Long Short-Term Memory model with spatiotemporal attention mechanism (CNN-BiLSTM-STA), is developed in this study. …”
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A multitask framework based on CA-EfficientNetV2 for the prediction of glioma molecular biomarkers by Qian Xu, Feng Ning Liang, Ya Ru Cao, Jin Duan, Teng Cui, Teng Zhao, Hong Zhu

“…Comparative analysis showed that our proposed model outperformed other convolutional neural network (CNN) - based approaches.ConclusionThe CA-EfficientNetV2-based multitask framework offers a robust, non-invasive method for preoperative prediction of glioma molecular markers. …”
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A Real-Time ETP Outlet Monitoring Framework Leveraging Environmental IoT, Colorimetry, and Learning Theory by Md. Jahid Hasan Mridha, Md. Mehedi Hossain, Sazid Md. Imran, Sk Ayub Al Wahid, Anika Tahsin, Md. Golam Rabiul Alam, Ashis Talukder, Ahmed Wasif Reza

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Real-Time Fire Risk Classification Using Sensor Data and Digital-Twin-Enabled Deep Learning by In-Seop Na, Vani Rajasekar, Velliangiri Sarveshwaran

“…Advanced deep learning architectures such as convolutional neural networks (CNNs), deep CNNs (DCNNs), and recurrent neural networks (RNNs) are utilized to identify critical spatial and temporal patterns in the data. …”
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Lateral Walking Gait Recognition and Hip Angle Prediction Using a Dual-Task Learning Framework by Mingxiang Luo, Meng Yin, Jinke Li, Ying Li, Worawarit Kobsiriphat, Hongliu Yu, Tiantian Xu, Xinyu Wu, Wujing Cao

“…We propose a dual-task learning framework, the “Twin Brother” model, which fuses convolutional neural network (CNN), long short-term memory (LSTM), neural networks (NNs), and the squeezing-elicited attention mechanism to classify the lateral gait stage and estimate the hip angle from electromyography (EMG) signals. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…To address these challenges, this study proposes a novel deep reinforcement learning (DRL)-based framework, integrating a convolutional neural network (CNN) for hierarchical feature extraction and a recurrent neural network (RNN) for sequential pattern recognition and time-series modeling. …”
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Explainable multi-view transformer framework with mutual learning for precision breast cancer pathology image classification by Haewon Byeon, Mahmood Alsaadi, Richa Vijay, Purshottam J. Assudani, Ashit Kumar Dutta, Monika Bansal, Pavitar Parkash Singh, Mukesh Soni, Mohammed Wasim Bhatt

“…This mutual learning framework enhances performance while also producing interpretable attention maps and feature-level visualizations that reveal the decision-making process of the model—promoting transparency, trust, and clinical usability. …”
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Challenges and prospects of artificial intelligence in aviation: a ​bibliometric study by Nuno Moura Lopes, Manuela Aparicio, Fátima Trindade Neves

“…Finally, a new conceptual framework was constructed based on the primary elements identified in the literature. …”
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Enhanced diabetic retinopathy detection using U-shaped network and capsule network-driven deep learning by Govindharaj I, Poongodai A, Gnanajeyaraman Rajaram, Santhakumar D, Ravichandran S, Vijaya Prabhu R, Udayakumar K, Yazhinian S

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Improving unsupervised pedestrian re‐identification with enhanced feature representation and robust clustering by Jiang Luo, Lingjun Liu

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Optimized Deep Learning for Mammography: Augmentation and Tailored Architectures by Syed Ibrar Hussain, Elena Toscano

“…This paper investigates the categorization of mammogram images into benign, malignant and normal categories, providing novel approaches based on Deep Convolutional Neural Networks to the early identification and classification of breast lesions. …”
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Prune and Distill: A Novel Knowledge Distillation Method for GCNs-Based Recommender Systems by Peng Yi, Zhaoxian Li, Lu Chen, Cheng Yang, Xiongcai Cai

“…Graph convolutional networks (GCNs)-based recommenders have demonstrated remarkable recommendation performances but suffer from prohibitive computational cost, limiting their practical deployment. …”
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Noise2Variance: Dual networks with variance constraint for self‐supervised real‐world image denoising by Hanlin Tan, Yu Liu, Maojun Zhang

“…A novel theoretical framework is introduced for training a basic CNN denoising model using three constraints: mean, variance, and augmentation. …”
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URDS: A Dual-Branch ViTs and CNNs Framework for Unpaired Raindrop and Rain Streak Removal by Nianyun Liu, Kebin Sha, Junwei Yan, Xinxi Xie

“…In this study, we propose a novel dual-branch GAN-based framework for unpaired rain detection and removal. …”
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SDMSEAF-YOLOv8: a framework to significantly improve the detection performance of unmanned aerial vehicle images by Linxuan Li, Xiaoyu Liu, Xuan Chen, Fengjuan Yin, Bin Chen, Yufeng Wang, Fanbin Meng

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