SVDDD: SAR Vehicle Target Detection Dataset Augmentation Based on Diffusion Model by Keao Wang, Zongxu Pan, Zixiao Wen

“…In the field of target detection using synthetic aperture radar (SAR) images, deep learning-based supervised learning methods have demonstrated outstanding performance. …”
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An Integrated Bearing Fault Diagnosis Method Based on Multibranch SKNet and Enhanced Inception-ResNet-v2 by Baoquan Hu, Jun Liu, Yue Xu, Tianlong Huo

“…Deep learning has recently received extensive attention in the field of rolling-bearing fault diagnosis owing to its powerful feature expression capability. …”
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Evaluation of the Risk of Recurrence in Patients with Local Advanced Rectal Tumours by Different Radiomic Analysis Approaches by Alaa Khadidos, Adil Khadidos, Olfat M. Mirza, Tawfiq Hasanin, Wegayehu Enbeyle, Abdulsattar Abdullah Hamad

“…Classically, researchers in this field of radiomics have used conventional machine learning techniques (random forest, for example). More recently, deep learning, a subdomain of machine learning, has emerged. …”
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Detection and Classification Method for Early-Stage Colorectal Cancer Using Dyadic Wavelet Packet Transform by Daigo Takano, Hajime Omura, Teruya Minamoto

“…Incorporating deep learning into computer-aided medical diagnosis has led to significant advancements. …”
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Remaining Useful Life Prediction of Milling Tool Based on Pyramid CNN by Ning Hu, Zhenguo Liu, Shixin Jiang, Quanzhou Li, Shuqi Zhong, Bingquan Chen

“…Predicting the RUL accurately can improve machining efficiency and the quality of product. Deep learning methods have strong learning capability in RUL prediction and are extensively used. …”
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Classification of ECG signals using deep neural networks by Nadour Mohamed, Cherroun Lakhmissi, Hadroug Nadji

“…The classification of ECG signals using deep learning techniques has garnered substantial interest in recent years; ECG classification tasks have exhibited promising outcomes with the application of deep learning models, particularly convolutional neural networks (CNNs). …”
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Vision-Based Object Recognition and Precise Localization for Space Body Control by Zeyu Shangguan, Lingyu Wang, Jianquan Zhang, Wenbo Dong

“…The contribution of this work is to introduce the deep-learning method for precision motion control and in the meanwhile ensure both the robustness and real time of the system. …”
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Introducing an ensemble method for the early detection of Alzheimer's disease through the analysis of PET scan images by Arezoo Borji, Taha-Hossein Hejazi, Abbas Seifi

“…In this paper, three deep-learning models, namely VGG16 and AlexNet, and a custom Convolutional Neural Network (CNN) with 8-fold cross-validation, have been used for classification. …”
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Comparison of In Silico Tools for Splice-Altering Variant Prediction Using Established Spliceogenic Variants: An End-User’s Point of View by Woori Jang, Joonhong Park, Hyojin Chae, Myungshin Kim

“…SpliceAI and SpliceRover, tools based on deep learning, outperformed all other tools, with AUCs of 0.972 and 0.924, respectively. …”
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Klasifikasi Teks Hadis Bukhari Terjemahan Indonesia Menggunakan Recurrent Convolutional Neural Network (CRNN) by Muhammad Yuslan Abu Bakar, Adiwijaya Adiwijaya

“…This research uses a hybrid method in deep learning by combining a Convolutional Neural Network and a Recurrent Neural Network, namely Convolutional Recurrent Neural Network (CRNN). …”
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Perspectives on Image Aesthetic Evaluation Techniques by Yang Kaiwei

“…Although deep learning technology can improve the accuracy of evaluation and has achieved some results in aesthetic evaluation tasks, the technology still faces challenges such as high subjectivity and poor diversity, and it is believed that with the progress of science and technology, these problems will be solved. …”
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Analysis of Intelligent Translation Systems and Evaluation Systems for Business English by Jianhong Chen

“…In order to improve the accuracy of automatic translation of business English, an optimized design of business English translation teaching platform is proposed based on the logistic model combined with deep learning. After using the logistic model to analyze the semantic features of business English translation, the deep learning model is used to segment and mine English images, and the automated lexical feature analysis of business English translation is carried out by using contextual feature matching and adaptive semantic variable finding methods to extract the amount of correlation features between words and vocabulary and to correct the differences in translation in a specific business context to improve the accuracy of English translation. …”
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Lightweight Cryptographic Algorithms for Guessing Attack Protection in Complex Internet of Things Applications by Mohammad Kamrul Hasan, Muhammad Shafiq, Shayla Islam, Bishwajeet Pandey, Yousef A. Baker El-Ebiary, Nazmus Shaker Nafi, R. Ciro Rodriguez, Doris Esenarro Vargas

“…For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications.…”
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A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet by Muhammad Waqas Ahmed, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz Alhammadi, Asaad Algarni, Ahmad Jalal, Jeongho Cho

“…Leveraging the power of deep learning, a DenseNet architecture achieves superior classification accuracy based on the optimized feature set. …”
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Fine-Grained Lung Cancer Classification from PET and CT Images Based on Multidimensional Attention Mechanism by RuoXi Qin, Zhenzhen Wang, LingYun Jiang, Kai Qiao, Jinjin Hai, Jian Chen, Junling Xu, Dapeng Shi, Bin Yan

“…Noninvasive computer-aided diagnosis can enable large-scale rapid screening of potential patients with lung cancer. Deep learning methods have already been applied for the automatic diagnosis of lung cancer in the past. …”
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Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System by Galib Muhammad Shahriar Himel, Md. Masudul Islam, Kh. Abdullah Al-Aff, Shams Ibne Karim, Md. Kabir Uddin Sikder

“…Skin cancer is a significant health concern worldwide, and early and accurate diagnosis plays a crucial role in improving patient outcomes. In recent years, deep learning models have shown remarkable success in various computer vision tasks, including image classification. …”
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Research and Analysis of Facial Recognition Based on FaceNet, DeepFace, and OpenFace by Li Minghan

“…This study provides a comprehensive review of recent advancements in face recognition technology, focusing on deep learning models such as FaceNet, DeepFace, and OpenFace. …”
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Inequality in breast cancer: Global statistics from 2022 to 2050 by Ling Liao

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Automatic classification of mobile apps to ensure safe usage for adolescents. by Hanadi Hakami

“…This work introduces an innovative approach utilizing Deep Learning techniques, specifically Attentional Convolutional Neural Networks (A-CNNs), for classifying M-APPs. …”
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Handwriting Digital Image Generation based on GAN: A Comparative Study of Basic GAN and CGAN Models by Zeng Hongzhi

“…The vast application of artificial intelligence in numerous fields—image generation being one of them—has been made possible by the quick development of deep learning. Generative Adversarial Networks (GAN) can generate high-quality images through an adversarial training mechanism. …”
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