Machine Learning and Deep Learning for Loan Prediction in Banking: Exploring Ensemble Methods and Data Balancing by Eslam Hussein Sayed, Amerah Alabrah, Kamel Hussein Rahouma, Muhammad Zohaib, Rasha M. Badry

“…Artificial Intelligence, using Machine Learning and Deep Learning techniques, can provide a more efficient solution. …”
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deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria by Yao Xiao, Yan Zhang

“…However, due to the complexity and variability of SECIS elements, recognition of all selenoprotein genes in bacteria is still a major challenge in the annotation of bacterial genomes. We have developed a deep learning-based algorithm to predict selenoprotein genes in bacterial genomic sequences, which demonstrates superior performance compared to currently available methods. …”
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Machine Learning Methods for Weather Forecasting: A Survey by Huijun Zhang, Yaxin Liu, Chongyu Zhang, Ningyun Li

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Overview of Applications and Research Directions of Deep Learning Methods for Wind Power Prediction by LIU Tan, LIU Na, LIU Guiping, LIU Kunjie, LIU Min, ZHUANG Xufei, ZHANG Zhonghao

“…This paper outlines the research objectives of wind power prediction from the classification of wind power prediction, the general idea of implementation, and the evaluation method. The application of deep learning technology in wind power prediction is reviewed, and on the basis of making a careful division of deep learning technology, it focuses on analyzing the overcome problems and performance by spatial structure-based deep learning models and time-based deep learning models and their related variants, and summarizes the limitations of the proposed modeling methods and the corresponding solutions. …”
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Advanced Deep Learning Methods to Generate and Discriminate Fake Images of Egyptian Monuments by Daniyah Alaswad, Mohamed A. Zohdy

“…This paper examines the performance of Generative Adversarial Networks (GAN), especially Style-Based Generator Architecture (StyleGAN), as a deep learning approach for producing realistic images of Egyptian monuments. …”
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PPDD: Egocentric Crack Segmentation in the Port Pavement with Deep Learning-Based Methods by Hyemin Yoon, Hoe-Kyoung Kim, Sangjin Kim

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Medical Image Segmentation: A Comprehensive Review of Deep Learning-Based Methods by Yuxiao Gao, Yang Jiang, Yanhong Peng, Fujiang Yuan, Xinyue Zhang, Jianfeng Wang

“…In recent years, with the widespread application of Convolutional Neural Networks (CNNs) in computer vision, deep learning-based methods for medical image segmentation have become a focal point of research. …”
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A survey of deep learning-based MRI stroke lesion segmentation methods by Weiyi YU, Tao CHEN, Junping ZHANG, Hongming SHAN

“…Automatic stroke lesion segmentation has become a research hotspot in recent years.In order to comprehensively review current progress of deep learning-based MRI stroke lesion segmentation methods, start with the clinical problems of stroke treatment, we further elaborate the research background and challenges of deep learning-based lesion segmentation, and introduce common public datasets (ISLES and ATLAS) for stroke lesion segmentation.Then, we focus on the innovation and progress of deep learning-based stroke lesion segmentation methods, and summarize the research progress from three perspectives: network structure, training strategy, and loss function, and compare the advantages and disadvantages of various methods.Finally, we discusse the difficulties and challenges in this research and its future development trend.…”
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A systematic review of deep learning methods for community detection in social networks by Mohamed El-Moussaoui, Mohamed Hanine, Ali Kartit, Monica Garcia Villar, Monica Garcia Villar, Monica Garcia Villar, Helena Garay, Helena Garay, Helena Garay, Isabel de la Torre Díez

“…Deep learning has emerged as an effective approach, offering robust capabilities to process large datasets, and uncover intricate relationships and patterns.MethodsIn this systematic literature review, we explore research conducted over the past decade, focusing on the use of deep learning techniques for community detection in social networks. …”
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Comparisons of different deep learning-based methods on fault diagnosis for geared system by Bing Han, Xiaohui Yang, Yafeng Ren, Wanggui Lan

“…The results show that the gear fault diagnosis method based on deep learning theory can effectively identify various gear faults under real test conditions. …”
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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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Detection of Mucous Retention Cysts Using Deep Learning Methods on Panoramic Radiographs by Seda Arslan Tuncer, Çağla Danacı, Sümeyye Coşgun Baybars

“…Aim: This study aimed to perform clinical diagnosis and treatment planning of mucous retention cysts with high accuracy and low error using the deep learning-based EfficientNet method. For this purpose, a hybrid approach that distinguishes healthy individuals from individuals with mucous retention cysts using panoramic radiographic images was presented.Material and Methods: Radiographs of patients who applied to the Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Fırat University between 2020 and 2022 and had panoramic radiography for various reasons were evaluated retrospectively. …”
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Research Progress of Dangerous Driving Behavior Recognition Methods Based on Deep Learning by Junjian Hou, Bingyu Zhang, Yudong Zhong, Wenbin He

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A Survey on Review Spam Detection Methods using Deep Learning Approach by Mahmoud Aliarab, Kazim Fouladi-Ghaleh

“…This paper reviews the proposed deep learning methods for the problem of review spam detection. …”
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An Overview of Integrating Deep Learning Methods With Close-Range Hyperspectral Imaging for Agriculture by Shah Faisal, Melanie Po-Leen Ooi, Ye Chow Kuang, Sanush K. Abeysekera, Dale Fletcher

“…Extracting spatial-spectral information of objects-of-interest from hyperspectral images requires sophisticated computational methods. The last decade saw the rapid advancement of deep learning methods due to their superior automatic feature extraction capability from images, and hence it is no surprise that these methods have been adapted and used for hyperspectral image analysis. …”
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Hybrid Deep Learning Methods for Human Activity Recognition and Localization in Outdoor Environments by Yirga Yayeh Munaye, Metadel Addis, Yenework Belayneh, Atinkut Molla, Wasyihun Admass

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Strategies to alleviate flickering: Bayesian and smoothing methods for deep learning classification in video by Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce Cox, Trevor Bihl

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Application of Deep Learning Methods for Employee Satisfaction Analysis Based on Text Data by A. A. Kazinets

“…The application of deep learning methods to analyze employee satisfaction based on text data is investigated. …”
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Research on Predicting Mine Earthquakes Based on Deep Learning Time-Series Methods by Xiufeng Zhang, Wei Li, Yang Chen, Junpeng Zou, Hangrui Zhang, Hao Wang, Chaohong Shi, Shaopeng Yan, Quan Zhang

“…To more accurately monitor and predict mine earthquakes and thereby reduce the potential risk they pose, this paper presents a study on the inversion and localization of seismic sources of mine earthquakes and a study on the prediction of mine earthquakes based on the deep learning method. The latter is set in the context of the Dongtan coal mine. …”
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Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models by John Fischer, Marko Orescanin, Justin Loomis, Patrick Mcclure

“…Aggregation strategies have been developed to pool or fuse the weights and biases of distributed deterministic models; however, modern deterministic deep learning (DL) models are often poorly calibrated and lack the ability to communicate a measure of epistemic uncertainty in prediction, which is desirable for remote sensing platforms and safety-critical applications. …”
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