Automated strabismus detection and classification using deep learning analysis of facial images by Mahsa Yarkheir, Motahhareh Sadeghi, Hamed Azarnoush, Mohammad Reza Akbari, Elias Khalili Pour

“…This research presents a new deep-learning-based approach for automatically identifying and classifying strabismus from facial images. …”
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Interpretable Deep Learning for Pneumonia Detection Using Chest X-Ray Images by Jovito Colin, Nico Surantha

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Prenatal depression level prediction using ensemble based deep learning model by Abinaya Gopalakrishnan, Xujuan Zhou, Revathi Venkataraman, Raj Gururajan, Ka Ching Chan, Guohun Zhu, Niall Higgins

“…Results:: We subsequently applied the ensemble based deep learning model on a testing dataset and our method proved to be 93.87 percent accurate, proving its superiority over the standard supervised classification models. …”
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Music Generation Using Deep Learning and Generative AI: A Systematic Review by Rohan Mitra, Imran Zualkernan

“…This paper presents a systematic review of recent advances in music generation using deep learning techniques, categorizing the latest research in the field and identifying key contributions from various approaches. …”
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Real-Time Prediction of the Trend of Ground Motion Intensity Based on Deep Learning by Tao Liu, Zhijun Dai

“…In order to predict the intensity of earthquake damage in advance and improve the effectiveness of earthquake emergency measures, this paper proposes a deep learning model for real-time prediction of the trend of ground motion intensity. …”
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USING ARTIFICIAL INTELLIGENCE (AI) AND DEEP LEARNING TECHNIQUES IN FINANCIAL RISK MANAGEMENT by Joseph Olorunfemi AKANDE

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Deep Learning Implementation Using CNN to Classify Bali God Sculpture Pictures by Ni Luh Gede Pivin Suwirmayanti, I Wayan Budi Sentana, I Ketut Gede Darma Putra, Made Sudarma, I Made Sukarsa, Komang Budiarta

“…The technique used in Deep Learning is Convolutional Neural Network (CNN). …”
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An Unsupervised Deep Learning Framework for Retrospective Gating of Catheter-Based Cardiac Imaging by Zheng Sun, Yue Yao, Ru Wang

“…The network was trained on clinical data sets in an unsupervised manner, addressing the difficulty of obtaining the gold standard in deep learning-based motion suppression techniques. Experimental results of in vivo intravascular ultrasound and optical coherence tomography sequences show that the proposed method has better performance in terms of motion artifact suppression and processing efficiency compared with the state-of-the-art nonlearning signal-based and IBG methods.…”
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Fake Detect: A Deep Learning Ensemble Model for Fake News Detection by Nida Aslam, Irfan Ullah Khan, Farah Salem Alotaibi, Lama Abdulaziz Aldaej, Asma Khaled Aldubaikil

“…Due to the nature of the dataset attributes, two deep learning models were used. For the textual attribute “statement,” Bi-LSTM-GRU-dense deep learning model was used, while for the remaining attributes, dense deep learning model was used. …”
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A Survey of Deep Learning Techniques for Arabic Aspect-Based Sentiment Analysis by Dalal Alqusair, Mounira Taileb, and Hassanin Al-Barhamtoshy

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Soil Classification Based on Deep Learning Algorithm and Visible Near-Infrared Spectroscopy by Xueying Li, Pingping Fan, Zongmin Li, Guangyuan Chen, Huimin Qiu, Guangli Hou

“…The aim of this study is to analyze the feasibility of land cover classification with small samples by convolutional neural network and, according to the deep learning algorithm, to explore new methods for rapid, nondestructive, and accurate classification of the land cover.…”
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Extraction of Fetal Electrocardiogram by Combining Deep Learning and SVD-ICA-NMF Methods by Said Ziani, Yousef Farhaoui, Mohammed Moutaib

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Multiview Multimodal Feature Fusion for Breast Cancer Classification Using Deep Learning by Sadam Hussain, Mansoor Ali Teevno, Usman Naseem, Daly Betzabeth Avendano Avalos, Servando Cardona-Huerta, Jose Gerardo Tamez-Pena

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Utilizing Age-Adaptive Deep Learning Approaches for Detecting Inappropriate Video Content by Iftikhar Alam, Abdul Basit, Riaz Ahmad Ziar

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Detection Method of Limb Movement in Competitive Sports Training Based on Deep Learning by Chunlin Qin, Shenglu Huo

“…In order to solve the above problems, a limb movement detection method in competitive sports training based on deep learning is proposed. The force change parameters of sports limb movements in the process of sports are computed to achieve the detection of limb movements in competitive sports training, and the limb movement characteristics in competitive sports training are extracted using a deep learning algorithm. …”
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Deep Learning and Multidisciplinary Imaging in Pediatric Surgical Oncology: A Scoping Review by M. A. D. Buser, J. K. van derRest, M. H. W. A. Wijnen, R. R. deKrijger, A. F. W. van derSteeg, M. M. van denHeuvel‐Eibrink, M. Reismann, S. Veldhoen, L. Pio, M. Markel

“…This indicates a need for advanced image processing technology such as Deep Learning (DL). Aim Our review focused on the use of DL in multidisciplinary imaging in pediatric surgical oncology. …”
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A parallel spatiotemporal deep learning network for highway traffic flow forecasting by Dongxiao Han, Juan Chen, Jian Sun

“…Experimental results confirm that the overall performance of our parallel spatiotemporal deep learning network surpasses those of other state-of-the-art methods.…”
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Deep learning helps discriminate between autoimmune hepatitis and primary biliary cholangitis by Alessio Gerussi, Oliver Lester Saldanha, Giorgio Cazzaniga, Damiano Verda, Zunamys I. Carrero, Bastian Engel, Richard Taubert, Francesca Bolis, Laura Cristoferi, Federica Malinverno, Francesca Colapietro, Reha Akpinar, Luca Di Tommaso, Luigi Terracciano, Ana Lleo, Mauro Viganó, Cristina Rigamonti, Daniela Cabibi, Vincenza Calvaruso, Fabio Gibilisco, Nicoló Caldonazzi, Alessandro Valentino, Stefano Ceola, Valentina Canini, Eugenia Nofit, Marco Muselli, Julien Calderaro, Dina Tiniakos, Vincenzo L’Imperio, Fabio Pagni, Nicola Zucchini, Pietro Invernizzi, Marco Carbone, Jakob Nikolas Kather

“…This study investigates the use of a deep learning (DL)-based pipeline for the diagnosis of AIH and PBC to aid differential diagnosis. …”
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GGSYOLOv5: Flame recognition method in complex scenes based on deep learning. by Fucai Sun, Liping Du, Yantao Dai

“…News of the fire is not uncommon, and fire has become the biggest hidden danger threatening the safety of public life and property. In this paper, a deep learning-based flame recognition method for complex scenes, GGSYOLOv5, is proposed. …”
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Reverse design of broadband sound absorption structure based on deep learning method by Yihong Zhou, Lifeng Ma, Xi Kang, Zhiyuan Zhu

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