A deep learning-based prognostic approach for predicting turbofan engine degradation and remaining useful life by Samiha M. Elsherif, Bassel Hafiz, M. A. Makhlouf, Osama Farouk

“…The proposed model utilizes an autoencoder followed by an LSTM layer with an attention mechanism, which focuses on the most relevant components of the sequences. A fully connected layer of the convolutional neural network is used to further process the important features. …”
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Enhancing Portfolio Optimization: A Two-Stage Approach with Deep Learning and Portfolio Optimization by Shiguo Huang, Linyu Cao, Ruili Sun, Tiefeng Ma, Shuangzhe Liu

“…In the first stage, we develop a stock trend prediction model for stock pre-selection called the AGC-CNN model, which leverages a convolutional neural network (CNN), self-attention mechanism, Graph Convolutional Network (GCN), and k-reciprocal nearest neighbors (k-reciprocal NN). …”
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Bitcoin price direction prediction using on-chain data and feature selection by Ritwik Dubey, David Enke

“…Bitcoin is the most traded cryptocurrency by volume and market cap. …”
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Analysis of Cardiac Arrhythmias Based on ResNet-ICBAM-2DCNN Dual-Channel Feature Fusion by Chuanjiang Wang, Junhao Ma, Guohui Wei, Xiujuan Sun

“…Cardiovascular disease (CVD) poses a significant challenge to global health, with cardiac arrhythmia representing one of its most prevalent manifestations. The timely and precise classification of arrhythmias is critical for the effective management of CVD. …”
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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. Following an extensive review of available solutions, algorithms, and networks based on this convolutional strategy, it was determined that the You Only Look Once algorithm in its version 8 (YOLOv8) would be the most suitable for object detection due to its performance and features. …”
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Use of Artificial Intelligence in Imaging Dementia by Manal Aljuhani, Azhaar Ashraf, Paul Edison

“…Alzheimer’s disease is the most common cause of dementia in the elderly population (aged 65 years and over), followed by vascular dementia, Lewy body dementia, and rare types of neurodegenerative diseases, including frontotemporal dementia. …”
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A Study on Using Transfer Learning to Utilize Information From Similar Systems for Data-Driven Condition Diagnosis and Prognosis by Marcel Braig, Peter Zeiler

“…Both concepts are implemented with the neural network types multilayer perceptron, 1D convolutional neural network, and temporal convolutional network. …”
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YOLO-GML: An object edge enhancement detection model for UAV aerial images in complex environments. by Zhihao Zheng, Jianguang Zhao, Jingjing Fan

“…Finally, we propose a Lightweight layered Shared Convolutional BN(LLSCB) Detection Head based on LSCD, so that the detection heads share the convolutional layer, and the BN is calculated independently, which improves the detection accuracy and reduces the number of parameters. …”
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HUMAN EMOTION RECOGNITION SYSTEM USING DEEP LEARNING ALGORITHMS by Kateryna Yuvchenko, Valentyn Yesilevskyi, Olena Sereda

“…An image classification method based on a densely connected convolutional neural network is also used. Results: the results of this work showed that the method of image classification, based on a densely connected convolutional neural network, is well suited for solving the problems of emotion recognition, because it has a fairly high accuracy. …”
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An urban road traffic flow prediction method based on multi-information fusion by Xiao Wu, Hua Huang, Tong Zhou, Yudan Tian, Shisen Wang, Jingting Wang

“…Then, a superimposed one-dimensional inflated convolutional layer is used to extract long-term trends, a dynamic graph convolutional layer to extract periodic features, and a short-term trend extractor to learn short-term temporal features. …”
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Reconsidering Authorship in the Ciceronian Corpus through Computational Authorship Attribution by Raija Vainio, Reima Välimäki, Anni Hella, Marjo Kaartinen, Teemu Immonen, Aleksi Vesanto, Filip Ginter

“…We use two classifiers, Support Vector Machine and Convolutional Neural Network, of which the latter is more accurate except in regard to certain aspects of vocabulary. …”
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Synergizing vision transformer with ensemble of deep learning model for accurate kidney stone detection using CT imaging by Arwa Alzughaibi, Adwan A. Alanazi, Mohammed Alshahrani, Ines Hilali Jaghdam, Abaker A. Hassaballa

“…Furthermore, the majority voting ensemble of three DL approaches, such as the graph convolutional network (GCN), temporal convolutional network (TCN), and three-dimensional convolutional autoencoder (3D-CAE) approaches, are employed to increase the precision and reliability of the kidney stone recognition. …”
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Modern technologies for hiding people's faces using object tracking based on YOLOv5 and DeepSort by А. Щур, О. Польшакова

“…This article provides a detailed overview of modern technologies and principles of tracking objects in video with assigning them unique elements. Since most video editors still leave most of the work to the user, it was decided to optimize this process. …”
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Preoperative assessment of tertiary lymphoid structures in stage I lung adenocarcinoma using CT radiomics: a multicenter retrospective cohort study by Xiaojiang Zhao, Yuhang Wang, Mengli Xue, Yun Ding, Han Zhang, Kai Wang, Jie Ren, Xin Li, Meilin Xu, Jun Lv, Zixiao Wang, Daqiang Sun

“…Tumor segmentation was achieved using an automatic virtual adversarial training segmentation algorithm based on a three-dimensional U-shape convolutional neural network (3D U-Net). Radiomic features were extracted from the tumor and peritumoral areas, with extensions of 2 mm, 4 mm, 6 mm, and 8 mm, respectively, and deep learning image features were extracted through a convolutional neural network. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…Leukemia, a blood malignancy, is one of the most prevalent cancer types affecting both adults and children. …”
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Saliency Aggregation: Multifeature and Neighbor Based Salient Region Detection for Social Images by Ye Liang, Congyan Lang, Jian Yu, Hongzhe Liu, Nan Ma

“…The popularity of social networks has brought the rapid growth of social images which have become an increasingly important image type. One of the most obvious attributes of social images is the tag. …”
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A Real-Time Green and Lightweight Model for Detection of Liquefied Petroleum Gas Cylinder Surface Defects Based on YOLOv5 by Burhan Duman

“…In resource-constrained devices, real-time speed, accuracy, and computational efficiency are the most critical requirements for defect detection. …”
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A multimodal deep learning model with differential evolution-based optimized features for classification of power quality disturbances by Md Nurul Islam

“…Differential evolution is used as an optimization tool to select the most relevant features and reduce the computational time. …”
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A novel anomaly detection method for multimodal WSN data flow via a dynamic graph neural network by Qinghao Zhang, Miao Ye, Xiaofang Deng

“…The simulation results obtained on a public dataset show that the proposed approach can significantly improve upon existing methods interms of robustness, and its F1 score reaches 0.90, which is 14.2% higher than that of the graph convolution network (GCN) with longshort-term memory (LSTM).…”
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Antifungal Activity and Cytotoxicity of Imidazole- and Morpholine-Based Lysosomotropic Detergents by Diana Hodyna, Vasyl Kovalishyn, Yurii Shulha, Olena Trokhimenko, Olesya Aksenovska, Sergiy Rogalsky, Larysa Metelytsia

“…To develop the QSAR models by the OCHEM platform, machine learning methods such as Transfor­mer Convolutional Neural Network (Trans-CNN), Transformer Convolutional Neural Fingerprint (Trans-CNF), and Random Forest (RF) were used. …”
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