Computer-Aided Diagnosis of Acute Lymphoblastic Leukemiaby Using a Novel CAE-CNN Framework by Mohammed Mansoor Alhammadi

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A novel end-to-end learning framework for inferring lncRNA-disease associations based on convolution neural network by Shunxian Zhou, Sisi Chen, Jinhai Le, Yangtai Xu, Lei Wang

“…IntroductionIn recent years, lots of computational models have been proposed to infer potential lncRNA-disease associations.MethodsIn this manuscript, we introduced a novel end-to-end learning framework named CNMCLDA, in which, we first adopted two convolutional neural networks to extract hidden features of diseases and lncRNAs separately. …”
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Design of mTCN framework for disaster prediction a fusion of massive machine type communications and temporal convolutional networks by M. Umadevi, J. Arun Kumar, S. Vishnu Priyan, C. Vivek

“…This study introduces the mTCN-FChain framework, a novel solution that combines Massive Machine-Type Communications (mMTC) and Temporal Convolutional Networks (TCNs) with federated learning and blockchain technology. …”
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An Integrative Framework for Healthcare Recommendation Systems: Leveraging the Linear Discriminant Wolf–Convolutional Neural Network (LDW-CNN) Model by Vedna Sharma, Surender Singh Samant, Tej Singh, Gusztáv Fekete

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A framework for continual learning in real-time traffic forecasting utilizing spatial–temporal graph convolutional recurrent networks by Mariam Labib Francies, Abeer Twakol Khalil, Hanan M. Amer, Mohamed Maher Ata

“…To address these challenges, this research presents an innovative framework known as the Continual Learning-based Spatial–Temporal Graph Convolutional Recurrent Neural Network (STGNN-CL) for persistent and accurate long-term traffic flow prediction. …”
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An integrated deep convolutional neural networks framework for the automatic segmentation and grading of glioma tumors using multimodal MRI scans by Otung John Peter Odong, Mohammed Abo-Zahhad, Moataz Abdelwahab

“…This study introduces an Integrated Deep Convolutional Neural Network (IDCNN)-based framework for segmenting and grading glioma tumors from multimodal MRI scans. …”
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A New Frontier in Wind Shear Intensity Forecasting: Stacked Temporal Convolutional Networks and Tree-Based Models Framework by Afaq Khattak, Jianping Zhang, Pak-wai Chan, Feng Chen, Abdulrazak H. Almaliki

“…This paper introduces a hybrid Temporal Convolutional Networks and Tree-Based Models (TCNs-TBMs) framework specifically designed for time series modeling and the prediction of wind shear intensity. …”
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Papayafreshnet: a hybrid deep learning framework for non-destructive freshness classification of papayas using convolutional and transformer networks by Ayan Sar, Tanupriya Choudhury, Tanmay Sarkar, Ketan Kotecha

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Artificial intelligence framework for lung cancer nodule segmentation and classification using convolutional neural network—from imaging to diagnosis by Ashwin Kumar Azhagarasan, Prashanthi Bhaskaran, Arunkumar Ramachandran, Kalpana Sivalingam

“…This study proposes an AI-based diagnostic framework integrating U-Net for lung nodule segmentation and a custom convolutional neural network (CNN) for binary classification of nodules as benign or malignant. …”
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Inverse link prediction with graph convolutional networks for knowledge-preserving sparsification in cheminformatics by Elnaz Bangian Tabrizi, Mehrdad Jalali, Mahboobeh Houshmand

“…This Inverse Link Prediction with Graph Convolutional Networks (ILP-GCN) framework offers a scalable and interpretable solution for cheminformatics, with broad applications in material discovery and beyond. …”
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A FRAMEWORK FOR MORPHOLOGICAL OPERATIONS USING COUNTER HARMONIC MEAN by Savya Sachi, D. Ganesh, Rajesh Tiwari, S. P. Manikanta, L. Bhagyalakshmi, Ankita Nigam, Sanjay Kumar Suman, Rajeev Shrivastava

“…In this article, we have a tendency to embrace a novel framework for learning morphological operations using counter-harmonic mean. …”
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Deep Time Series Intelligent Framework for Power Data Asset Evaluation by Lihong Ge, Xin Li, Li Wang, Jian Wei, Bo Huang

“…In response to this challenge, this paper proposes a new deep learning framework, namely Time-Series Convolutional Memory Efficient Network (TSENet). …”
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A Spatio-Temporal Joint Diagnosis Framework for Bearing Faults via Graph Convolution and Attention-Enhanced Bidirectional Gated Networks by Zhiguo Xiao, Xinyao Cao, Huihui Hao, Siwen Liang, Junli Liu, Dongni Li

“…To address these challenges, this paper proposes a joint diagnosis framework integrating graph convolutional networks (GCNs) with attention-enhanced bidirectional gated recurrent units (BiGRUs). …”
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Performance Evaluation of 3-D Convolutional Neural Network for Multitemporal Flood Classification Framework With Synthetic Aperture Radar Image Data by Dodi Sudiana, Indra Riyanto, Mia Rizkinia, Rahmat Arief, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo, Ketut Wikantika

“…This study proposes a novel approach using synthetic aperture radar (SAR) sensors, which can penetrate clouds, to classify flooded urban areas. The framework employs a 3-D convolutional neural network (3-D CNN) to process multitemporal SAR data from Sentinel-1 (S-1). …”
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FedBFGCN: A Graph Federated Learning Framework Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution by Hefei Wang, Ruichun Gu, Jingyu Wang, Xiaolin Zhang, Hui Wei

“…To address this issue, this paper proposes an innovative graph federated learning framework called FedBFGCN (Graph Federated Learning Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution) to optimize the embedding and analysis efficiency of graph data. …”
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A topology-guided high-quality solution learning framework for security-constraint unit commitment based on graph convolutional network by Liqian Gao, Lishen Wei, Shichang Cui, Jiakun Fang, Xiaomeng Ai, Wei Yao, Jinyu Wen

“…In this sense, this paper proposes a topology-guided high-quality solution learning framework based on graph convolutional network (GCN) and neighborhood search (NS). …”
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FibroRegNet: A Regression Framework for the Pulmonary Fibrosis Prognosis Prediction Using a Convolutional Spatial Transformer Network by Pardhasaradhi Mittapalli, V. Thanikaiselvan

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AI-Powered Convolutional Neural Network Surrogate Modeling for High-Speed Finite Element Analysis in the NPPs Fuel Performance Framework by Salvatore A. Cancemi, Andrius Ambrutis, Mantas Povilaitis, Rosa Lo Frano

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Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles by Fatma S. Alrayes, Nazir Ahmad, Asma Alshuhail, Menwa Alshammeri, Ali Alqazzaz, Hassan Alkhiri, Jehad Saad Alqurni, Yahia Said

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Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

“…Building upon the RT-DETR framework, this study proposes a Multiscale Separable Deformable (MSD) module that integrates depthwise convolution with deformable convolution to enhance feature extraction capabilities while reducing computational load. …”
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