Image Reconstruction for High-Performance Electrical Capacitance Tomography System Using Deep Learning by Yanpeng Zhang, Deyun Chen

“…An optimization model for imaging is generated as a powerful optimizer for building a computational model to ameliorate the reconstruction accuracy. Based on the deep learning methodology, the previous images reconstructed by using one of the imaging techniques to the required images are abstracted and stored in the deep learning machine, resulting in an error rate of 8.9%, and this is considered good on ECT. …”
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Enhanced hybrid attention deep learning for avocado ripeness classification on resource constrained devices by Sumitra Nuanmeesri

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Physical-aware model accuracy estimation for protein complex using deep learning method by Haodong Wang, Meng Sun, Lei Xie, Dong Liu, Guijun Zhang

“…In this work, we propose a physical-aware deep learning method, DeepUMQA-PA, to evaluate the residue-wise quality of protein complex models. …”
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Synthetic Computed Tomography generation using deep-learning for female pelvic radiotherapy planning by Rachael Tulip, Sebastian Andersson, Robert Chuter, Spyros Manolopoulos

“…Synthetic Computed Tomography (sCT) is required to provide electron density information for MR-only radiotherapy. Deep-learning (DL) methods for sCT generation show improved dose congruence over other sCT generation methods (e.g. bulk density). …”
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Data Homogeneity Effect in Deep Learning-Based Prediction of Type 1 Diabetic Retinopathy by Jui-En Lo, Eugene Yu-Chuan Kang, Yun-Nung Chen, Yi-Ting Hsieh, Nan-Kai Wang, Ta-Ching Chen, Kuan-Jen Chen, Wei-Chi Wu, Yih-Shiou Hwang, Fu-Sung Lo, Chi-Chun Lai

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Automated Fillet Weld Inspection Based on Deep Learning from 2D Images by Ignacio Diaz-Cano, Arturo Morgado-Estevez, José María Rodríguez Corral, Pablo Medina-Coello, Blas Salvador-Dominguez, Miguel Alvarez-Alcon

“…The object detection method follows a geometric deep learning model based on convolutional neural networks. …”
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A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data by Vasileios Skaramagkas, Ioannis Kyprakis, Georgia S. Karanasiou, Dimitris I. Fotiadis, Manolis Tsiknakis

Subjects: “…Deep learning…”
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A systematic mapping study of source code representation for deep learning in software engineering by Hazem Peter Samoaa, Firas Bayram, Pasquale Salza, Philipp Leitner

“…Abstract The usage of deep learning (DL) approaches for software engineering has attracted much attention, particularly in source code modelling and analysis. …”
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Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis by Hajar Moradmand, Lei Ren

“…This study proposes a multistage deep learning model to predict the Overall Sharp Score (OSS) from hand X-ray images. …”
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A Hybrid Deep Learning Method for the Estimation of the State of Health of Lithium-Ion Batteries by Shuo Cheng

“…Compared to other complex deep learning (DL) methods, the VIT-GRU significantly outperforms them, according to the RMSE and MAE of the predicted values.…”
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Deep Learning Methods for Arabic Autoencoder Speech Recognition System for Electro-Larynx Device by Zinah J. Mohammed Ameen, Abdulkareem Abdulrahman Kadhim

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Deep Learning-Based Remote Sensing Image Analysis for Wildfire Risk Evaluation and Monitoring by Shiying Yu, Minerva Singh

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Auditing the clinical usage of deep-learning based organ-at-risk auto-segmentation in radiotherapy by Josh Mason, Jack Doherty, Sarah Robinson, Meagan de la Bastide, Jack Miskell, Ruth McLauchlan

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Deep Learning in Music Generation: A Comprehensive Investigation of Models, Challenges and Future Directions by Kong Xiangchen

“…Deep learning has made a lot of progress in the field of music generation. …”
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ELECTRICITY PRICE FORECASTING IN TURKISH DAY-AHEAD MARKET VIA DEEP LEARNING TECHNIQUES by Arif Arifoğlu, Tuğrul Kandemir

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A deep learning-driven multi-layered steganographic approach for enhanced data security by Yousef Sanjalawe, Salam Al-E’mari, Salam Fraihat, Mosleh Abualhaj, Emran Alzubi

“…At the same time, the deep learning encoder adds layer of protection by concealing an image within another. …”
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Deep learning improves physician accuracy in the comprehensive detection of abnormalities on chest X-rays by Pamela G. Anderson, Hannah Tarder-Stoll, Mehmet Alpaslan, Nora Keathley, David L. Levin, Srivas Venkatesh, Elliot Bartel, Serge Sicular, Scott Howell, Robert V. Lindsey, Rebecca M. Jones

“…Here, we present an FDA-cleared, artificial intelligence (AI) system which uses a deep learning algorithm to assist physicians in the comprehensive detection and localization of abnormalities on chest X-rays. …”
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A multi-modal dental dataset for semi-supervised deep learning image segmentation by Yaqi Wang, Fan Ye, Yifei Chen, Chengkai Wang, Chengyu Wu, Feng Xu, Zhean Ma, Yi Liu, Yifan Zhang, Mingguo Cao, Xiaodiao Chen

“…Panoramic X-ray images (PXI) and Cone Beam Computed Tomography (CBCT) are key tools for dentists in diagnosing and treating dental conditions. Additionally, deep learning for tooth segmentation can focus on relevant treatment information and localize lesions. …”
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Recent Advancements in Deep Learning Frameworks for Precision Fish Farming Opportunities, Challenges, and Applications by Gaganpreet Kaur, Nirmal Adhikari, Singamaneni Krishnapriya, Surindar Gopalrao Wawale, R. Q. Malik, Abu Sarwar Zamani, Julian Perez-Falcon, Jonathan Osei-Owusu

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Hybrid Deep Learning for Gas Price Prediction Using Multi-Factor and Temporal Features by Shuliang Zhang, Hao Wu, Jin Wang, Longsheng Du

“…In this paper, we innovatively apply k-means clustering to analyze the correlations of multiple factors affecting natural gas prices and design a hybrid deep learning model that integrates both multi-factor and time series features. …”
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