Deep and Reinforcement Learning Technologies on Internet of Vehicle (IoV) Applications: Current Issues and Future Trends by Lina Elmoiz Alatabani, Elmustafa Sayed Ali, Rania A. Mokhtar, Rashid A. Saeed, Hesham Alhumyani, Mohammad Kamrul Hasan

“…In this paper, some concepts related to deep learning networks will be discussed as one of the uses of machine learning in IoV systems, in addition to studying the effect of neural networks (NNs) and their types, as well as deep learning mechanisms that help in processing large amounts of unclassified data. …”
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Diabetes Prediction Through Linkage of Causal Discovery and Inference Model with Machine Learning Models by Mi Jin Noh, Yang Sok Kim

“…<b>Methods</b>: Kaggle’s dataset from the National Institute of Diabetes and Digestive and Kidney Diseases was analyzed using logistic regression, deep learning, gradient boosting, and decision trees. …”
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A Novel and Effective Model for Automatic Modulation Classification Prediction Based on Multi-BIGRU, Multi-Encoder, and Hyper-Cross by Jianzheng Lin

“…Automatic Modulation Classification (AMC) is a pivotal technology in various communication systems. In recent years, deep learning (DL) has been widely applied in AMC methods due to its powerful feature extraction capabilities. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…This paper addresses this gap by proposing a novel IDS that utilizes hybrid feature selection and deep learning classifiers to detect FDIAs in smart grids. …”
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Barlow Twins deep neural network for advanced 1D drug–target interaction prediction by Maximilian G. Schuh, Davide Boldini, Annkathrin I. Bohne, Stephan A. Sieber

“…By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. …”
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Film Recommender System Menggunakan Metode Neural Collaborative Filtering by Ni’mah Khoiriyah Ayyiyah, Retno Kusumaningrum, Rismiyati Rismiyati

“…Penelitian ini menggunakan pendekatan prediksi Collaborative Filtering dengan mengimplementasikan deep learning berdasarkan teknologi Neural Collaborative Filtering pada dataset MovieLens. …”
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PREDICTING USD/ TL EXCHANGE RATE IN TURKEY: THE LONG-SHORT TERM MEMORY APPROACH by Abdul-razak Bawa Yussif, Fatih Mangır, Zeynep Karaçor, Ayten Yağmur

“…In order to perform a more accurate exchange rate prediction, deep-learning methods have been employed withremarkable rates of success. …”
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Image experience prediction for historic districts using a CNN-transformer fusion model by Youping Teng, Weijia Wang

“…The results highlight the practical potential of deep learning in visual sentiment analysis and emphasize the importance of emotional value in improving experiences in historic districts. …”
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Lie Detection Technology of Bimodal Feature Fusion Based on Domain Adversarial Neural Networks by Yan Zhou, Feng Bu

“…First, a deep learning neural network was used as a feature extractor to isolate speech and facial expression features exhibited by the liars. …”
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Efficient Lane Detection Technique Based on Lightweight Attention Deep Neural Network by Zhiting Yao, Xiyuan Chen

“…For self-driving vehicles, detecting lane lines in changeable scenarios is a fundamental yet challenging task. The rise of deep learning in recent years has contributed to the thriving of autonomous driving. …”
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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

“…Recent advancements in deep learning have significantly improved medical image segmentation. …”
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Learning by making – student-made models and creative projects for medical education: systematic review with qualitative synthesis by Tan Yong Yi, Panwar Shreyans, Ranganath Vallabhajosyula

“…Creative projects facilitated deep learning objectives via interdisciplinary learning and promoted new ways of perceiving concepts. …”
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Penerapan Deep Convolutional Generative Adversarial Network Untuk Menciptakan Data Sintesis Perilaku Pengemudi Dalam Berkendara by Michael Stephen Lui, Fitra Abdurrachman Bachtiar, Novanto Yudistira

“…Penggunaan sensor visual memiliki performa yang lebih baik ketika menggunakan metode deep learning. Salah satu metode untuk meningkatkan performa metode deep learning adalah dengan menggunakan data sintesis hasil model generatif sebagai tambahan data. …”
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Multisegment Mapping Network for Massive MIMO Detection by Yongzhi Yu, Jianming Wang, Limin Guo

“…However, the use of deep learning for massive MIMO detection can achieve a high degree of computational parallelism, and deep learning constitutes an important technical approach for solving the signal detection problem. …”
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Efficient Data Augmentation Methods for Crop Disease Recognition in Sustainable Environmental Systems by Saebom Lee, Sokjoon Lee

“…Geometric transformations and color space augmentation techniques are applied to validate the efficiency of deep learning models, specifically convolution and transformer models, in recognizing multiple crop diseases. …”
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Predicted Anchor Region Proposal with Balanced Feature Pyramid for License Plate Detection in Traffic Scene Images by Hoanh Nguyen

“…License plate detection is a key problem in intelligent transportation systems. Recently, many deep learning-based networks have been proposed and achieved incredible success in general object detection, such as faster R-CNN, SSD, and R-FCN. …”
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Klasifikasi Aktivitas Manusia Menggunakan Metode Long Short-Term Memory by Latansa Nurry Izza Afida, Fitra Abdurrachman Bachtiar, Imam Cholissodin

“…Sehingga pada penelitian ini menerapkan dataset primer dengan menggunakan label kelas sebanyak 16 sehingga diusulkan metode deep learning Long Short Term Memory (LSTM). Proses penelitian dimulai dari pengambilan data, preprocessing data, modelling dan perbandingan algoritma deep learning LSTM dan machine learning KNN. …”
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Compensating CBCT Motion Artifacts with Any 2D Generative Model by Yipeng Sun, Linda-Sophie Schneider, Mingxuan Gu, Siyuan Mei, Siming Bayer, Andreas K. Maier

“…Leveraging two-dimensional (2D) generative models while ensuring consistency between adjacent CBCT slices, our method addresses the limitations of traditional deep learning approaches that process each 2D slice of a three-dimensional (3D) volume independently. …”
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Robust Face Detection and Identification under Occlusion using MTCNN and RESNET50 by Eiman Wahab, Wajeeha Shafique, Habiba Amir, Sameena Javed, Muhammad Marouf

“…By leveraging the capabilities in the deep learning algorithms, this project provides a robust solution for automating the recognition of partially occluded faces. …”
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A Full Stage Data Augmentation Method in Deep Convolutional Neural Network for Natural Image Classification by Qinghe Zheng, Mingqiang Yang, Xinyu Tian, Nan Jiang, Deqiang Wang

“…Nowadays, deep learning has achieved remarkable results in many computer vision related tasks, among which the support of big data is essential. …”
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