Convolutional neural network for IT lung diagnostics by U. A. Vishniakou, T. He

“…The experiments were carried out on the Android service framework platform, which is divided into two parts: Android front-end and server. …”
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Digital Twin Framework Using Real-Time Asset Tracking for Smart Flexible Manufacturing System by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…Furthermore, the CNN combined with the ADAM optimizer produced the best results, with a mean squared error of 0.83. The framework also utilized a deep reinforcement learning algorithm. …”
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Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

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Deep Learning Framework for Predicting Transonic Wing Buffet Loads Due to Structural Eigenmode-Based Deformations by Rebecca Zahn, Moritz Zieher, Christian Breitsamter

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Dynamic Q value wavelet transform for IF estimation and seizure detection via QT plane-CNN framework by Amaya Rose Abraham, Anurag Nishad, Mihir Jaipuria, Abhay Upadhyay, Sudeep Baudha

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StyleGraph: A Heterogeneous Graph Neural Framework for Stylistic and Semantic Rumor Detection on Social Media by Haider Jaffar, Ali Mohades, Mohammad Ebrahim Shiri

“…This study introduced StyleGraph, a novel graph-based framework that enhances rumor detection by jointly leveraging semantic and stylistic information. …”
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A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images by Mishmala Sushith, A. Sathiya, V. Kalaipoonguzhali, V. Sathya

“…This paper presents a novel hybrid deep learning framework that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for diabetic retinopathy (DR) early detection and progression monitoring using retinal fundus images. …”
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DeepRNAac4C: a hybrid deep learning framework for RNA N4-acetylcytidine site prediction by Guohua Huang, Guohua Huang, Runjuan Xiao, Runjuan Xiao, Chunying Peng, Jinyun Jiang, Weihong Chen

“…To address these challenges, we propose DeepRNAac4C, a deep learning framework for RNA ac4C sites prediction. DeepRNAac4C integrates residual neural networks, convolutional neural networks (CNN), bidirectional long short-term memory networks (BiLSTM), and bidirectional gated recurrent units (BiGRU) to effectively capture both local and global sequence features. …”
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An Integrated CNN-BiLSTM-Transformer Framework for Improved Anomaly Detection Using Surveillance Videos by Sarfaraz Natha, Mohammad Siraj, Fareed Ahmed, Majid Altamimi, Muslim Syed

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A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial resolution by Davide Consoli, Leandro Parente, Rolf Simoes, Murat Şahin, Xuemeng Tian, Martijn Witjes, Lindsey Sloat, Tomislav Hengl

“…Addressing this issue, we developed TSIRF (Time-Series Iteration-free Reconstruction Framework), a computational framework that can be used to apply diverse time-series processing tasks, such as temporal aggregation and time-series reconstruction by simply adjusting the convolution kernel. …”
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Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection by Md. Najmul Mowla, Davood Asadi, Shamsul Masum, Khaled Rabie

“…This enhanced framework addresses prior challenges by integrating adaptive pooling, concatenated convolutions for multi-scale feature extraction, and an improved attention mechanism incorporating shared fully connected layers, Glorot initialization, rectified linear units (ReLU), layer normalization, and attention-gating. …”
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Enhanced People Re-identification in CCTV Surveillance Using Deep Learning: A Framework for Real-World Applications by Mossaab Idrissi Alami, Abderrahmane Ez-zahout, Fouzia Omary

“…In this paper, we propose a robust deep learning framework that leverages convolutional neural networks (CNNs) with a customized triplet loss function to overcome these obstacles and improve re-identification accuracy. …”
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Large Scale Land Cover Mapping in Ontario, Canada, Using a Deep Learning Framework by Fariba Mohammadimanesh

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Deep Learning Framework for Oil Shale Pyrolysis State Recognition Using Bionic Electronic Nose by Yuping Yuan, Xiaohui Weng, Yuheng Qiao, Xiaohu Shi, Zhiyong Chang

“…Experimental results demonstrate the superiority of our proposed framework, highlighting its effectiveness and advantages over existing methods.…”
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An Ensemble Hybrid Framework: A Comparative Analysis of Metaheuristic Algorithms for Ensemble Hybrid CNN Features for Plants Disease Classification by Khaoula Taji, Ali Sohail, Tariq Shahzad, Bilal Shoaib Khan, Muhammad Adnan Khan, Khmaies Ouahada

“…The extracted Convolutional Neural Network (CNN) features are selected and fused with the LBP features. …”
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Kinematic Adaptive Frame Recognition (KAFR): A Novel Framework for Video Segmentation via Frame Similarity and Surgical Tool Tracking by Huu Phong Nguyen, Shekhar Madhav Khairnar, Sofia Garces Palacios, Amr Al-Abbas, Melissa E. Hogg, Amer H. Zureikat, Patricio M. Polanco, Herbert J. Zeh, Ganesh Sankaranarayanan

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EmbryoNet-VGG16 framework for deep learning-based embryo classification with Otsu segmentation by M. Saraniya, J. Anitha Ruth

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A Novel CNN-Based Framework for Detection and Classification of Power Quality Disturbances: Exploring Multi-Class Versus Multi-Label Classification by Aleksandra Zlatkova, Dimitar Taskovski

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SeqConv-Net: A Deep Learning Segmentation Framework for Airborne LiDAR Point Clouds Based on Spatially Ordered Sequences by Bin Guo, Chunjing Yao, Hongchao Ma, Jie Wang, Junhao Xu

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BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers by Cheng Lv, Xu-Jun Shu, Xu-Jun Shu, Quan Liang, Jun Qiu, Zi-Cheng Xiong, Jing bo Ye, Shang bo Li, Cheng Qing Liu, Jing Zhen Niu, Sheng-Bo Chen, Hong Rao

“…Recently, deep learning technologies, particularly Convolutional Neural Networks (CNN), have achieved breakthrough advances in medical image analysis, offering a new paradigm for automated precise diagnosis. …”
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