Application of Machine Learning Technologies for Managing Multifactor Threats in an Integrated Model of Cognitive Security Center at Defense Industry Enterprise by Pavel Panilov, Tatiana Tsibizova

“…This article provides a detailed examination of key elements of this model, including data analysis, anomaly detection, threat response, classification and optimization, as well as the notification system. …”
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A comprehensive deep learning approach to improve enchondroma detection on X-ray images by Ayhan Aydin, Caner Ozcan, Safak Aydın Simsek, Ferhat Say

“…The images were then annotated by orthopedic oncology specialists using advanced, state-of-the-art object detection algorithms trained with diverse architectural frameworks. …”
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Emotion Detection and Student Engagement in Distance Learning During Containment Due to the COVID-19 by Benyoussef Abdellaoui, Ahmed Remaida, Zineb Sabri, Younes EL BOUZEKRI EL IDRISSI, Aniss Moumen

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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…Sophisticated algorithms were developed and implemented to improve the accuracy of fire detection while minimizing false alarms. …”
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FedDL: personalized federated deep learning for enhanced detection and classification of diabetic retinopathy by Dasari Bhulakshmi, Dharmendra Singh Rajput

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Epileptic Seizure Detection Using Machine Learning: A Systematic Review and Meta-Analysis by Lin Bai, Gerhard Litscher, Xiaoning Li

“…This meta-analysis reviews the performance of ML models in seizure detection and analyzes factors such as the model type (deep learning vs. traditional ML), data preprocessing methods, and dataset types. …”
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Research progress of deep learning-based object detection of optical remote sensing image by Yurong LIAO, Haining WANG, Cunbao LIN, Yang LI, Yuqiang FANG, Shuyan NI

“…Object detection is the core issue in the interpretation of optical remote sensing images, and it is widely used in fields such as intelligence reconnaissance, target monitoring, and disaster rescue.Firstly, combined with the research progress of deep learning optical remote sensing image object detection algorithms, the two types of algorithms based on candidate regions and regression analysis were reviewed.Secondly, the improvement of object detection algorithms for four types of common task-specific scenes were summarized, including rotating objects, small objects, multi-scales, and dense objects.Then, combined with commonly used remote sensing image data sets, the performance of different algorithms was compared and analyzed.Finally, the issues worthy of attention in remote sensing image object detection in the future were prospected, and ideas for follow-up related research were provided.…”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…To address class imbalance, synthetic minority oversampling technique (SMOTE) was applied. Several machine learning algorithms, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees, Random Forests, and Neural Networks, were implemented and evaluated. …”
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Review of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learning by Berk Özel, Muhammad Shahab Alam, Muhammad Umer Khan

“…Utilizing image processing, computer vision, and deep learning algorithms, we can now detect fires with exceptional accuracy and respond promptly to mitigate their impact. …”
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A Review of Intrusion Detection for Railway Perimeter Using Deep Learning-Based Methods by Jin Wang, Hongyang Zhai, Yang Yang, Niuqi Xu, Hao Li, Di Fu

“…In addition, the application status of semantic segmentation and object detection algorithms based on deep learning in detecting railway perimeter intrusion is explored, including the classification, principles, and performance of the algorithms in practical applications. …”
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Integrating Handcrafted Features with Machine Learning for Hate Speech Detection in Albanian Social Media by Fetahi Endrit, Hamiti Mentor, Susuri Arsim, Zenuni Xhemal, Ajdari Jaumin

“…We utilized several machine-learning algorithms, including Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), and Logistic Regression (LR), and extracted a considerable number of handcrafted features. …”
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Orga-Dete: An Improved Lightweight Deep Learning Model for Lung Organoid Detection and Classification by Xuan Huang, Qin Gao, Hanwen Zhang, Fuhong Min, Dong Li, Gangyin Luo

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Integrating Radar-Based Obstacle Detection with Deep Reinforcement Learning for Robust Autonomous Navigation by Nabih Pico, Estrella Montero, Maykoll Vanegas, Jose Miguel Erazo Ayon, Eugene Auh, Jiyou Shin, Myeongyun Doh, Sang-Hyeon Park, Hyungpil Moon

“…This study presents an approach to autonomous navigation for wheeled robots, combining radar-based dynamic obstacle detection with a BiGRU-based deep reinforcement learning (DRL) framework. …”
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Parkinson’s disease detection using inceptionV3: A Deep learning approach by Pallavi M. Shanthappa, Madhwesh Bayari, G.B. Abhilash, K.V. Gokul, P.J. Ashish

“…This study uses deep learning algorithms to classify spiral images traced by patients as an inexpensive diagnostic technique for the detection of PD. …”
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Deep Learning in Glaucoma Detection and Progression Prediction: A Systematic Review and Meta-Analysis by Xiao Chun Ling, Henry Shen-Lih Chen, Po-Han Yeh, Yu-Chun Cheng, Chu-Yen Huang, Su-Chin Shen, Yung-Sung Lee

“…<b>Results:</b> A total of 48 studies were included in the meta-analysis. DL algorithms demonstrated high diagnostic performance in glaucoma detection using fundus photography and OCT images. …”
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Big data for imaging assessment in glaucoma by Douglas R. da Costa, Felipe A. Medeiros

“…With the rapid development of computational technologies, artificial intelligence (AI) and deep learning (DL) algorithms are emerging as potential tools for screening, diagnosing, and monitoring glaucoma progression. …”
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A novel dataset and deep learning object detection benchmark for grapevine pest surveillance by Giorgio Checola, Paolo Sonego, Roberto Zorer, Valerio Mazzoni, Franca Ghidoni, Alberto Gelmetti, Pietro Franceschi

“…Additionally, we tested the impact of altering image resolution and data augmentation, while also addressing potential issues related to class detection. …”
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Automated snow cover detection on mountain glaciers using spaceborne imagery and machine learning by R. Aberle, E. Enderlin, S. O'Neel, C. Florentine, L. Sass, A. Dickson, H.-P. Marshall, A. Flores

“…We develop the image classifiers by testing numerous machine learning algorithms with training and validation data from the U.S. …”
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Smart Tool-Related Faults Monitoring System Using Process Simulation-Based Machine Learning Algorithms by Arash Ebrahimi Araghizad, Faraz Tehranizadeh, Kemal Kilic, Erhan Budak

“…To further enhance the capabilities of the proposed fault monitoring system, process-related and machine-related faults will be investigated in future research. Several machine learning algorithms will be explored as well as additional data sources will be integrated in order to enhance the accuracy and reliability of fault detection.…”
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Empowering Retail Through Advanced Consumer Product Recognition Using Aquila Optimization Algorithm With Deep Learning by Mohammed Alghamdi, Hanan Abdullah Mengash, Mohammed Aljebreen, Mohammed Maray, Abdulbasit A. Darem, Ahmed S. Salama

“…Therefore, this study presents Advanced Consumer Product Recognition using the Aquila Optimization Algorithm with Deep Learning (ACPR-AOADL) technique. …”
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