Review of communication optimization methods in federated learning by YANG Zhikai, LIU Yaping, ZHANG Shuo, SUN Zhe, YAN Dingyu

“…With the development and popularization of artificial intelligence technologies represented by deep learning, the security issues they continuously expose have become a huge challenge affecting cyberspace security. …”
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Integrating Macroeconomic and Technical Indicators into Forecasting the Stock Market: A Data-Driven Approach by Saima Latif, Faheem Aslam, Paulo Ferreira, Sohail Iqbal

“…We propose three hybrid deep learning models that sequentially combine convolutional and recurrent neural networks for improved feature extraction and predictive accuracy. …”
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Optimized sequential model for superior classification of plant disease by Yogesh Chimate, Sangram Patil, K. Prathapan, Jaydeep Patil, Jayendra Khot

“…Deep learning architectures, like convolutional neural network, can autonomously learn and extract complicated characteristics and patterns from huge datasets. …”
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Optimalisasi Hyper Parameter Convolutional Neural Networks Menggunakan Ant Colony Optimization by Fian Yulio Santoso, Eko Sediyono, Hindriyanto Dwi Purnomo

“…Salah satu metode tersebut menggabungkan convolutional neural networks (CNN) dengan deep learning, tetapi hyperparameter, seperti fungsi loss, fungsi aktivasi, dan optimizers, memengaruhi kinerjanya. …”
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Comparative use of different AI methods for the prediction of concrete compressive strength by Mouhamadou Amar

“…The most accurate model was found to be a gradient-boosted tree followed by deep learning and random forest. Forecasts were validated with high accuracy by comparing experimental results to numerical data.…”
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Improving Medical Image Quality Using a Super-Resolution Technique with Attention Mechanism by Dong Yun Lee, Jang Yeop Kim, Soo Young Cho

“…The model uses L1 loss to generate realistic and smooth outputs, outperforming existing deep learning methods in capturing contours and textures. …”
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Detection of cervical cell based on multi-scale spatial information by Gang Li, Xinyu Fan, Chuanyun Xu, Pengfei Lv, Ru Wang, Zihan Ruan, Zheng Zhou, Yang Zhang

“…Abstract Cervical cancer poses a significant health risk to women. Deep learning methods can assist pathologists in quickly screening images of suspected lesion cells, greatly improving the efficiency of cervical cancer screening and diagnosis. …”
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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

“…Additionally, this research opens avenues for optimizing deep learning models and leveraging edge computing technologies to reduce response times in wearable device applications.…”
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Ancient Stone Inscription Image Denoising and Inpainting Methods Based on Deep Neural Networks by Haoming Zhang, Yue Qi, Xiaoting Xue, Yahui Nan

“…For ancient stone inscriptions, we should obtain more perfect digital results without multiple types of noise, while there are few deep learning methods designed for processing stone inscription images. …”
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XTNSR: Xception-based transformer network for single image super resolution by Jagrati Talreja, Supavadee Aramvith, Takao Onoye

“…This paper presents a Deep Learning model for single-image super-resolution. …”
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Virtual Healthcare Center for COVID-19 Patient Detection Based on Artificial Intelligence Approaches by Seifeddine Messaoud, Soulef Bouaafia, Amna Maraoui, Lazhar Khriji, Ahmed Chiheb Ammari, Mohsen Machhout

“…However, technological tests based on deep learning techniques and medical images could be useful in fighting this pandemic. …”
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Functional feature extraction and validation from twelve-lead electrocardiograms to identify atrial fibrillation by Wei Yang, Rajat Deo, Wensheng Guo

“…Abstract Background Deep learning methods on standard, 12-lead electrocardiograms (ECG) have resulted in the ability to identify individuals at high-risk for the development of atrial fibrillation. …”
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Digital Core Modeling Based on Pretrained Generative Adversarial Neural Networks by Qing Zhang, Benqiang Wang, Xusheng Liang, Yizhen Li, Feng He, Yuexiang Hao

“…With the development of deep learning technology, a variety of deep learning algorithms have been applied to digital core modeling. …”
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Cardiac sound classification using a hybrid approach: MFCC-based feature fusion and CNN deep features by Mahbubeh Bahreini, Ramin Barati, Abbas Kamali

“…This paper presents a novel approach to PCG signal classification, leveraging a fusion of deep learning features and handcrafted features based on mutual information measurements. …”
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Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution by Keivan Faghih Niresi, Chong-Yung Chi

“…Recently, it has been shown that deep learning is a promising approach to image denoising. …”
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FABLDroid: Malware detection based on hybrid analysis with factor analysis and broad learning methods for android applications by Kazım Kılıç, İsmail Atacak, İbrahim Alper Doğru

“…Applications installed from third-party environments threaten users’ privacy and security. Deep learning-based methods are popular for detecting Android malware. …”
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Implementation Of Convolutional Neural Network (Cnn) Based On Mobile Application For Rice Quality Determination by Muhammad Zainal Altim, Abdullah Basalamah, kasman kasman

“…The purpose of this study is to design and build a CNN deep learning program modeling for a mobile application for rice quality classification and analyze the performance of a mobile application-based classification program as a means of halal information in real time. …”
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Dynamic Spatial–Temporal Graph Neural Network for Cooling Capacity Prediction in HVDC Systems by Hao Sun, Shaosen Li, Jianxiang Huang, Hao Li, Guanxin Jing, Ye Tao, Xincui Tian

“…The proposed method demonstrates superior performance over traditional machine learning and deep learning baselines on real-world cooling system data. …”
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Squeeze-and-Excitation Vision Transformer for Lung Nodule Classification by Xiaozhong Xue, Yanhe Ma, Weiwei Du, Yahui Peng

“…This study combines 2 attention mechanisms and proposes a novel deep learning model called squeeze-and-excitation vision transformer (SE-ViT). …”
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A large histological images dataset of gastric cancer with tumour microenvironment annotation for AI by Shenghan Lou, Jianxin Ji, Huiying Li, Xuan Zhang, Yang Jiang, Menglei Hua, Kexin Chen, Kaiyuan Ge, Qi Zhang, Liuying Wang, Peng Han, Lei Cao

“…Additionally, we explained two deep learning models used as validation examples using this dataset.…”
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