Detection of Flexible Pavement Surface Cracks in Coastal Regions Using Deep Learning and 2D/3D Images by Carlos Sanchez, Feng Wang, Yongsheng Bai, Haitao Gong

“…Developments in artificial intelligence and machine learning (AI/ML) can aid in the progress of more robust and precise detection algorithms. …”
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LULC change detection and future LULC modelling using RF and MLPNN-Markov algorithms in the uMngeni catchment, KwaZulu-Natal, South Africa by Orlando Bhungeni, Michael Gebreslasie, Ashadevi Ramjatan

“…Thus, the adoption of remote sensing data and Machine Learning Algorithms (MLAs) is a novel approach that provides spatiotemporal data on the environmental changes resulting from LULC dynamics. …”
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High sensitivity in spontaneous intracranial hemorrhage detection from emergency head CT scans using ensemble-learning approach by Juuso Takala, Heikki Peura, Riku Pirinen, Katri Väätäinen, Sergei Terjajev, Ziyuan Lin, Rahul Raj, Miikka Korja

“…Although the success of DL algorithms depends on multiple factors, including training data versatility and quality of annotations, using the proposed ensemble-learning approach and rule-based post-processing may help clinicians to develop highly accurate DL solutions for clinical imaging diagnostics.…”
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Deep learning-based optical coherence tomography and retinal images for detection of diabetic retinopathy: a systematic and meta analysis by Zheng Bi, Jinju Li, Qiongyi Liu, Zhaohui Fang, Zhaohui Fang

“…ObjectiveTo systematically review and meta-analyze the effectiveness of deep learning algorithms applied to optical coherence tomography (OCT) and retinal images for the detection of diabetic retinopathy (DR).MethodsWe conducted a comprehensive literature search in multiple databases including PubMed, Cochrane library, Web of Science, Embase and IEEE Xplore up to July 2024. …”
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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

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A Fast and Effective MIMO Algorithm Using CLR-RNN for Hybrid MDM and WDM Optical Communication System by Danni Zhang, Zhongwei Tan, Xinyuan Ma, Shun Lu, Wenhua Ren, Fengping Yan

“…The results show that the introduction of an adaptive machine learning model in MIMO detection for WDM-MDM optical transmission systems can significantly improve the quality of the transmitted signals and achieve better performance than other MIMO detection algorithms while maintaining a faster computational speed and a lower number of parameters.…”
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Exploring deep learning for landslide mapping: A comprehensive review by Zhi-qiang Yang, Wen-wen Qi, Chong Xu, Xiao-yi Shao

“…Recent advancements in high-resolution satellite imagery, coupled with the rapid development of artificial intelligence, particularly data-driven deep learning algorithms (DL) such as convolutional neural networks (CNN), have provided rich feature indicators for landslide mapping, overcoming previous limitations. …”
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Identification of Spambots and Fake Followers on Social Network via Interpretable AI-Based Machine Learning by Danish Javed, Noor Zaman Zaman, Navid Ali Khan, Sayan Kumar Ray, Arafat Al-Dhaqm, Victor R. Kebande

“…To this end, we propose an interpretable machine learning (ML) framework, leveraging multiple ML algorithms with hyperparameters optimized through cross-validation, to enhance the detection process. …”
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Unmanned Aerial Vehicle Path Planning in Complex Dynamic Environments Based on Deep Reinforcement Learning by Jiandong Liu, Wei Luo, Guoqing Zhang, Ruihao Li

“…Concurrently, a novel data storage system for deep Q-networks (DQN), named dynamic data memory (DDM), is introduced to hasten the learning process and convergence for UAVs. …”
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Enhancing Security of Databases through Anomaly Detection in Structured Workloads by Charanjeet Dadiyala, Faijan Qureshi, Kritika Anil Bhattad, Sourabh Thakur, Nida Tabassum Sharif Sheikh, Kushagra Anil Kumar Singh

“…The present research utilized the Isolation Forest algorithm to detect outliers in high-dimensional data sets. …”
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Enhancing Security of Databases through Anomaly Detection in Structured Workloads by Charanjeet Dadiyala, Faijan Qureshi, Kritika Anil Bhattad, Sourabh Thakur, Nida Tabassum Sharif Sheikh, Kushagra Anil Kumar Singh

“…The present research utilized the Isolation Forest algorithm to detect outliers in high-dimensional data sets. …”
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Refining daily precipitation estimates using machine learning and multi-source data in alpine regions with unevenly distributed gauges by Huajin Lei, Hongyi Li, Hongyu Zhao

“…Meanwhile, XDMF is a promising algorithm for enhancing precipitation in high-altitude mountain areas, which can be flexibly transferred to other regions, different machine learning algorithms, and various hydrometeorological variables.…”
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FPGA-oriented lightweight multi-modal free-space detection network by Feiyi Fang, Junzhu Mao, Wei Yu, Jianfeng Lu

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Rotating Machinery Fault Detection Using Support Vector Machine via Feature Ranking by Harry Hoa Huynh, Cheol-Hong Min

“…Especially the use of machine learning algorithms has been very popular in all areas, including fault detection. …”
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Analisis Visual dan Machine Learning untuk Mengukur Validitas Dokumen Akademik Perpustakaan: Studi pada Data Turnitin by Hesti Ari Wardani, Imam Yuadi

“…This study aims to analyze the distribution of Turnitin results in academic library documents from various study programs at Universitas Nasional, Jakarta. Using a data visualization approach and machine learning algorithms, this research explores the relationship between Turnitin scores and document validity status. …”
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DDFNet: A Dual-Domain Fusion Network for Robust Synthetic Speech Detection by Jing Lu, Qiang Zhang, Jialu Cao, Hui Tian

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Enhancing the prediction of vitamin D deficiency levels using an integrated approach of deep learning and evolutionary computing by Ahmed Alzahrani, Muhammad Zubair Asghar

“…This work proposes a novel approach to detect VDD levels by combining deep learning techniques with evolutionary computing (EC). …”
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Unveiling shadows: A data-driven insight on depression among Bangladeshi university students by Sanjib Kumar Sen, Md. Shifatul Ahsan Apurba, Anika Priodorshinee Mrittika, Md. Tawhid Anwar, A.B.M. Alim Al Islam, Jannatun Noor

“…To achieve these objectives, a survey was meticulously designed in collaboration with psychologists, counselors, and therapists. Seven machine learning models, including Support Virtual Machine (SVM), K-Nearest Neighbor (K-NN), Gaussian Naive Bayes (GNB), Decision Tree (DT), Random Forest Classifier (RFC), Artificial Neural Network (ANN), and Gradient Boosting (GB), were trained and tested using the collected data (n = 750) to identify the most effective method for predicting depression. …”
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Detecting sand gradation based on the two-dimensional sand particle features in sand images by Chuanyun Xu, Heng Wang, Yang Zhang, Song Sun, Gang Li

“…Although traditional vibration sieving methods are highly reliable, they are inefficient. Existing machine learning-based automated detection methods have limited accuracy, and deep learning is hindered by difficulties in image data annotation and the lack of high-quality datasets, which affect its application effectiveness.To address this, this paper proposes a detection method based on the two-dimensional sand particle features in sand images. …”
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LSTM‐based real‐time stress detection using PPG signals on raspberry Pi by Amin Rostami, Koorosh Motaman, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

“…This article presents an innovative methodology employing deep learning algorithms on the Raspberry Pi 3, a platform distinguished by its cost‐effectiveness and limited resources. …”
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