AI-Based Anomaly Detection and Optimization Framework for Blockchain Smart Contracts by Hassen Louati, Ali Louati, Elham Kariri, Abdulla Almekhlafi

“…The framework integrates Neural Architecture Search (NAS) to automatically design optimal Convolutional Neural Network (CNN) architectures tailored to blockchain data, enabling effective anomaly detection. …”
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Digital Holographic Reconstruction Based on Deep Learning Framework With Unpaired Data by Da Yin, Zhongzheng Gu, Yanran Zhang, Fengyan Gu, Shouping Nie, Jun Ma, Caojin Yuan

“…Convolutional neural network (CNN) has great potentials in holographic reconstruction. …”
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An interpretable deep learning framework for medical diagnosis using spectrogram analysis by Shagufta Henna, Juan Miguel Lopez Alcaraz, Upaka Rathnayake, Mohamed Amjath

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An RIS-Assisted Integrated Deep Learning Framework for MIMO-OFDM-IM by Md Abdul Aziz, Md Habibur Rahman, Mohammad Abrar Shakil Sejan, Rana Tabassum, Hyoung-Kyu Song

“…To address this challenge, we propose InDeep, a robust deep learning (DL)-based detection framework designed for RIS-assisted MIMO-OFDM-IM systems. …”
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Multimodal Data Fusion Framework for Early Prediction of Autism Spectrum Disorder by Mohemmed Sha, Hussein Al-Dossary, Mohamudha Parveen Rahamathulla

“…The proposed framework consists of four modules such as stacked bidirectional long short-term memory (SBiLSTM) using attention mechanism for representing text/numerical features, multilevel 2D-convolutional neural network–gated recurrent units (ABM-2D-CNN–GRUs) using attention mechanism for extracting facial features, and multimodal factorized bilinear (MFB) pooling for combining the features. …”
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A novel Swin transformer based framework for speech recognition for dysarthria by Rabbia Mahum, Ismaila Ganiyu, Lotfi Hidri, Ahmed M. El-Sherbeeny, Haseeb Hassan

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BGNER: A boundary guidance framework for enhanced named entity recognition by Yu He, Li Sun, Qianyu Yue, Haitao Wu, Xiaojuan Wang

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A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

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A robust deep learning framework for multiclass skin cancer classification by Burhanettin Ozdemir, Ishak Pacal

“…The Proposed Model demonstrates exceptional accuracy and generalizability across diverse skin lesion classes, establishing a reliable framework for early and accurate skin cancer diagnosis in clinical practice.…”
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High-accuracy PM2.5 prediction via mutual information filtering and Bayesian-Optimized Spatio-Temporal Convolutional Networks by Wanyu Wang

“…This optimizer explores multiple potential optima in the parameter space concurrently, enabling efficient global hyperparameter search and improving model robustness to noise.Third, an Information Screening-Enhanced Spatiotemporal Convolutional Network (MIBO-STCN) is introduced. Building on our prior STCN framework that integrates causal convolution and adaptive receptive fields, this architecture embeds an information screening layer to achieve synergistic optimization of spatiotemporal dependency modeling and redundancy reduction. …”
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Hybrid deep learning framework for real-time DO prediction in aquaculture by Longqin Xu, Wenjun Liu, Cai Chengqing, Tonglai Liu, Xuekai Gao, Ferdous Sohel, Murtaza Hasan, Mansour Ghorbanpour, Shahbaz Gul Hassan, Shuangyin Liu

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AI-Enabled Condition Monitoring Framework for Autonomous Pavement-Sweeping Robots by Sathian Pookkuttath, Aung Kyaw Zin, Akhil Jayadeep, M. A. Viraj J. Muthugala, Mohan Rajesh Elara

“…This study introduces an AI-driven condition monitoring (CM) framework designed to detect terrain unevenness and slope gradients in real time, distinguishing between safe and unsafe conditions. …”
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Interface-aware molecular generative framework for protein–protein interaction modulators by Jianmin Wang, Jiashun Mao, Chunyan Li, Hongxin Xiang, Xun Wang, Shuang Wang, Zixu Wang, Yangyang Chen, Yuquan Li, Kyoung Tai No, Tao Song, Xiangxiang Zeng

“…Based on this, we propose a novel molecular generative framework tailored to PPI interfaces, named GENiPPI. …”
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Design and implementation of quantum hippo inspired convolutional neural networks using parametric quantum circuits for an efficient lung cancer classification by S. Radhika, G. Sharada

“…The proposed learning framework consists of four components namely Data collection & Data pre-processing, Classical Hippo Optimized Convolutional Neural networks, and Quantum based model using parametric quantum circuits (PQC), Evaluation and Analysis. …”
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Assessing english Language teachers’ pedagogical effectiveness using convolutional neural networks optimized by modified virus colony search algorithm by Li Zhang

“…A comprehensive index framework is developed, comprising five primary dimensions: instructional design, instructional materials, teaching methods and approaches, teaching effectiveness, and classroom management. …”
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Convolutional Neural Network–Vision Transformer Architecture with Gated Control Mechanism and Multi-Scale Fusion for Enhanced Pulmonary Disease Classification by Okpala Chibuike, Xiaopeng Yang

“…This hybrid approach offers a promising framework for reliable and accurate disease diagnosis in medical imaging.…”
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Inference of three-dimensional hot-spot and shell morphology in inertial confinement fusion experiments using a convolutional neural network by K. M. Woo, J. Buck, K. Churnetski, R. Betti, C. A. Thomas, C. Stoeckl, P. V. Heuer, C. Kanan, P. B. Radha, J. Carroll-Nellenback, K. S. Anderson, T. J. B. Collins, L. Ceurvorst, V. Gopalaswamy, S. T. Ivancic

“…This work demonstrates a CNN framework that successfully reconstructs 3D capsule structures from two-dimensional images in ICF implosions.…”
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Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer by J.-S. Chou, H.-M. Nguyen, H.-P. Phan, K.-L. Wang

“…This research contributes to developing predictive early warning systems for deep-seated landslide displacement by employing advanced computational models for environmental risk management. The novel framework evaluates machine learning, time series deep learning, and convolutional neural networks (CNNs), identifying the most effective models to be enhanced by the Age of Exploration-Inspired Optimizer (AEIO) algorithm. …”
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Bridge Damage Identification Using Time-Varying Filtering-Based Empirical Mode Decomposition and Pre-Trained Convolutional Neural Networks by Shenghuan Zeng, Jian Cui, Ding Luo, Naiwei Lu

“…This study presents a bridge damage identification framework integrating time-varying filtering-based empirical mode decomposition (TVFEMD) with pre-trained convolutional neural networks (CNNs). …”
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Ensuring Food Security and Biodiversity: A Novel Convolutional Neural Network (CNN) for Early Detection of Plant Disease in Precision Agriculture by Md Jiabul Hoque, Md. Saiful Islam, Mahadi Hassan, Mohammad Minhazul Islam

“…In addition, a new Convolutional Neural Network (CNN) structure, which achieves a higher accuracy (99.05%) compared to pre-existing models, is shown. …”
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