Research Progress of Dangerous Driving Behavior Recognition Methods Based on Deep Learning by Junjian Hou, Bingyu Zhang, Yudong Zhong, Wenbin He

“…RNN possesses the capability to process sequential data effectively; however, training these networks is challenging. …”
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Deep learning-driven brain tumor classification and segmentation using non-contrast MRI by Nan-Han Lu, Yung-Hui Huang, Kuo-Ying Liu, Tai-Been Chen

“…Non-contrast T1-weighted (T1w) and T2-weighted (T2w) images were combined with their average to form RGB three-channel inputs, enriching the representation for model training. …”
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Implementation of Automatic Segmentation Framework as Preprocessing Step for Radiomics Analysis of Lung Anatomical Districts by Alessandro Stefano, Fabiano Bini, Nicolò Lauciello, Giovanni Pasini, Franco Marinozzi, Giorgio Russo

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Predicting housing price, housing density, and green area coverage from combined satellite and street view imagery using deep learning by Ana Beatriz de Figueiredo Oliveira, Mauro Castelli, Esra Suel

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Deep learning-based artificial intelligence for assisting diagnosis, assessment and treatment in soft tissue sarcomas by Ruiling Xu, Jinxin Tang, Chenbei Li, Hua Wang, Lan Li, Yu He, Chao Tu, Zhihong Li

“…Besides, the reinforcement of the model by transfer learning and generative adversarial network (GAN) for data augmentation has also been elaborated. …”
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Facial and Neck Region Analysis for Deepfake Detection Using Remote Photoplethysmography Signal Similarity by Byeong Seon An, Hyeji Lim, Hyeon Ah Seong, Eui Chul Lee

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Evaluation of Brain Function Recovery After Traumatic Brain Injury Treatment in a Porcine Model by Cross-Group Temporal–Spatial Correlation Analysis by Wenwu Sun, William Reeves, Madison M. Fagan, Christina B. Welch, Kelly M. Scheulin, Sydney E. Sneed, Todd R. Callaway, Kylee J. Duberstein, Franklin D. West, Qun Zhao

“…By applying machine learning techniques—specifically, independent component analysis and sparse dictionary learning—across seven identified resting-state networks, we assessed the temporal and spatial correlations indicative of treatment efficacy. …”
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Morningness and Conscientiousness: A Meta-analysis, Online Survey and Resting fMRI Study by Debore Buzoku, Sahar Esmat, Ray Norbury

“…Further, survey report and resting-state functional Magnetic Resonance Imaging (rs-fMRI, N = 43) indicated that the relationship between morningness and conscientiousness was moderated by functional connectivity with the Default Mode Network (DMN). …”
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Application of Artificial Intelligence in Retinopathy of Prematurity From 2010 to 2023: A Bibliometric Analysis by Jing Gao, Na Fang, Yao Xu

“…Data analysis and visualization were performed using Bibliometrix and VOSviewer, covering publications, journals, authors, institutions, countries, collaboration networks, keywords, and trending topics. …”
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Modélisation du changement d’échelles en télédétection par une méthode neuronale : application a l’étude de l’évolution de l’occupation hivernale des sols en Bretagne... by Thomas Houet, Laurence Hubert-Moy, Grégoire Mercier

“…Therefore, observed changes have to be validated from a local scale analysis. The aim of this study is to develop a method that enables the assessment of high or low variations detected at a regional scale from SPOT VEGETATION images with data registered at a higher scale, SPOT HRVIR images in this case. …”
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Principles and metrics of extreme learning machines using a highly nonlinear fiber by Hary Mathilde, Brunner Daniel, Leybov Lev, Ryczkowski Piotr, Dudley John M., Genty Goëry

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Detection of Alzheimer Disease in Neuroimages Using Vision Transformers: Systematic Review and Meta-Analysis by Vivens Mubonanyikuzo, Hongjie Yan, Temitope Emmanuel Komolafe, Liang Zhou, Tao Wu, Nizhuan Wang

“…The included papers used ViT models for AD detection versus healthy controls based on neuroimaging data, and the included studies used magnetic resonance imaging and positron emission tomography. …”
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Container Security in Cloud Environments: A Comprehensive Analysis and Future Directions for DevSecOps by Santosh Ugale, Amol Potgantwar

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Predicting Sugarcane Yield Through Temporal Analysis of Satellite Imagery During the Growth Phase by Julio Cezar Souza Vasconcelos, Caio Simplicio Arantes, Eduardo Antonio Speranza, João Francisco Gonçalves Antunes, Luiz Antonio Falaguasta Barbosa, Geraldo Magela de Almeida Cançado

“…This research investigates how to estimate sugarcane (<i>Saccharum officinarum</i> L.) yield at harvest by using an average satellite image time-series collected during the growth phase. …”
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ANALYSIS OF THE INFLUENCE OF SOCIAL CAPITAL ON ENTREPRENEURIAL ORIENTATION AND ENTREPRENEURIAL BEHAVIOR: A STUDY ON STARTUPS IN JABODETABEK by Rendy Gunawan, Novita Ikasari

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Enhanced Rolling Bearing Fault Diagnosis Using Multimodal Deep Learning and Singular Spectrum Analysis by Yunhang Wang, Hongwei Wang, Ruoyang Bai, Yuxin Shi, Xicong Chen, Qingang Xu

“…Based on this, a recursive gated convolutional neural network (RGCNN) is designed to process the STFT image data, while a 1D convolutional neural network (1DCNN) is specifically optimized for training with time series data. …”
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Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

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Near-Infrared Hyperspectral Target Tracking Based on Background Information and Spectral Position Prediction by Li Wu, Mengyuan Wang, Weixiang Zhong, Kunpeng Huang, Wenhao Jiang, Jia Li, Dong Zhao

“…Meanwhile, for visible spectrum (VIS) data analysis, the architecture maintains competitive effectiveness with a 59.6% success rate and 78.8% precision.…”
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Prognosis of COVID-19 Using Artificial Intelligence: A Systematic Review and Meta-analysis by Saeed Reza Motamedian, Negin Cheraghi, Sadra Mohaghegh, Elham Babadi Oregani, Mahrsa Amjadi, Parnian Shobeiri, Niusha Solouki, Nikoo Ahmadi, Yassine Bouchareb, Arman Rahmim

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Steganography in IoT: A Comprehensive Survey on Approaches, Challenges, and Future Directions by Maha Driss, Lamia Berriche, Safa Ben Atitallah, Siwar Rekik

“…This study bridges this gap by providing a comprehensive review of steganographic methods for IoT, exploring approaches across many domains such as spatial, frequency, and hybrid methods used in images, videos, audio, text, network traffic, hybrid approaches, and quantum-based methods. …”
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