The Choice of Training Data and the Generalizability of Machine Learning Models for Network Intrusion Detection Systems by Marcin Iwanowski, Dominik Olszewski, Waldemar Graniszewski, Jacek Krupski, Franciszek Pelc

“…Network Intrusion Detection Systems (NIDS) driven by Machine Learning (ML) algorithms are usually trained using publicly available datasets consisting of labeled traffic samples, where labels refer to traffic classes, usually one benign and multiple harmful. …”
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Machine learning-based detection of medical service anomalies: Kazakhstan’s health insurance data by Maksut Kulzhanov, Alexander Wagner, Abylkair Skakov, Iliyas Mukhamejan, Saya Zhorabek, Ainur B. Qumar

“…This research aims to apply advanced ML algorithms to analyze data from the Republic of Kazakhstan’s Obligatory Health Insurance Fund (OHIF) and automatically detect anomalies in the structure of delivered medical services. …”
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Semisupervised Learning for Detecting Inverse Compton Emission in Galaxy Clusters by Sheng-Chieh Lin, Yuanyuan Su, Fabio Gastaldello, Nathan Jacobs

“…Anomaly detection is performed on the validation and test data sets consisting of 2T spectra as the normal set and 1T+IC spectra as anomalies. …”
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Deep reinforced cognitive analytics algorithm (DRCAM): An advanced method to early detection of cognitive skill impairment using deep learning and reinforcement learning by Sunita Patil, Dr. Swetta Kukreja

“…Improvement in accuracy and intervention with discussable efficacy and potential for explanation is seen when benchmarked against conventional cognition. • Proposed the Deep Reinforced Cognitive Analytics Algorithm (DRCAM) for multimodal data. • The proposed model outperforms traditional models in cognitive skill impairment detection. • Demonstrated scalability for diverse healthcare datasets.…”
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Advances in machine learning for the detection and characterization of microplastics in the environment by M. Maksuda Khanam, M. Khabir Uddin, Julhash U. Kazi

“…Recent advances in machine learning (ML) have revolutionized the field of microplastic research by automating and enhancing detection processes. …”
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Forest age estimation using UAV-LiDAR and Sentinel-2 data with machine learning algorithms- a case study of Masson pine (Pinus massoniana) by Jinjin Chen, Xuejian Li, Zihao Huang, Jie Xuan, Chao Chen, Mengchen Hu, Cheng Tan, Yongxia Zhou, Yinyin Zhao, Jiacong Yu, Lei Huang, Meixuan Song, Huaqiang Du

“…Three machine learning algorithms, Adaptive Boosting (AdaBoost), Random Forest (RF), and Extreme Random Tree (ERT), are used to predict forest age in a Masson pine (Pinus massoniana Lamb.) forest. …”
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A Tunnel Surface Diseases Detection Algorithm Based on YOLOv4 by LI Jia, QIU Xinhua, JI Yuwen

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MACHINE LEARNING TECHNIQUES FOR RETINOPATHY DETECTION IN DIABETIC PATIENTS by Ajay Kushwaha, Ahankari Sachin Suresh, Chennoju Phanindra, Anil Kumar Sahu, Devanand Bhonsle, Yamini Chouhan

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An Assembled Feature Attentive Algorithm for Automatic Detection of Waste Water Treatment Plants Based on Multiple Neural Networks by Cong Li, Zhengchao Chen, Zhuonan Huang, Yue Shuai, Shaohua Wang, Xiangkun Qi, Jiayi Zheng

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Pulmonary Nodules Detection Algorithm Combining Multi-view and Attention Mechanism by LIU Yu-bo, LIU Guo-zhu, SHI Cao, XU Can-hui

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Leveraging the Louvain algorithm for enhanced group formation and collaboration in online learning environments by Minkyung Lee, Priya Sharma

“…The results indicate that algorithmically detected groups exhibit strong internal communication and cohesiveness, as evidenced by high clustering coefficients, density values, and weighted degrees. …”
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A Novel Skin Cancer Detection Approach Using Deep Learning Algorithm with Image Segmentation Filters by Awf A. Ramadhan, Omer S. Kareem, Diyar Q. Zeebaree

“…This paper presents a deep learning model based on the convolutional neural network algorithm to provide automatic detection of skin cancer. …”
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ContourTL-Net: Contour-Based Transfer Learning Algorithm for Early-Stage Brain Tumor Detection by N. I. Md. Ashafuddula, Rafiqul Islam

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Photovoltaic fault detection algorithm using ensemble learning enhanced with deep neural network feature engineering by Maryam Parvin, Hossein Yousefi, Behnam Mohammadi-Ivatloo

“…This paper introduces an innovative methodology that integrates advanced deep neural network (DNN)-based feature extraction with ensemble learning (EL) to achieve precise fault detection in PV systems under limited training data availability. …”
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Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations by Constantinos Halkiopoulos, Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou

“…<b>Background/Objectives</b>: The following systematic review integrates neuroimaging techniques with deep learning approaches concerning emotion detection. It, therefore, aims to merge cognitive neuroscience insights with advanced algorithmic methods in pursuit of an enhanced understanding and applications of emotion recognition. …”
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Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems by Saud S. Alotaibi, Turki Ali Alghamdi

“…This study presents a League Championship Algorithm Feature Selection with Optimal Deep Learning based Cyberattack Detection (CLAFS-ODLCD) technique for securing the digital ecosystem. …”
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Comparison of Deep Learning Models and Optimization Algorithms in the Detection of Scoliosis and Spondylolisthesis from X-Ray Images by Abdullah Erhan Akkaya, Cengiz Hark, Harun Güneş

“…This study aims to classify spine X-ray images according to three possible conditions (Normal, Scoliosis, and Spondylolisthesis) and to exploit the potential of these X-ray images to detect possible diseases occurring in the spine. The performance of deep learning models and optimization algorithms used in this process was evaluated. …”
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A Fused Multiscale Pictorial Sequence Learning Mechanism Applied to Pavement Detection by Zhang Jiazhen, Wang Xiulai, Zhao Shuxu

“…Considering that most pavement anomaly detection algorithms are difficult to play a stable role in data related to different distributions of pavement anomalies, this paper proposes a pavement anomaly detection algorithm based on multi-scale fusion time series information. …”
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Facial expression deep learning algorithms in the detection of neurological disorders: a systematic review and meta-analysis by Shania Yoonesi, Ramila Abedi Azar, Melika Arab Bafrani, Shayan Yaghmayee, Haniye Shahavand, Majid Mirmazloumi, Narges Moazeni Limoudehi, Mohammadreza Rahmani, Saina Hasany, Fatemeh Zahra Idjadi, Mohammad Amin Aalipour, Hossein Gharedaghi, Sadaf Salehi, Mahsa Asadi Anar, Mohammad Saeed Soleimani

“…Objectives This systematic review and meta-analysis aimed to evaluate the performance of deep learning algorithms in detecting facial expression changes for diagnosing neurological disorders. …”
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Supervised machine learning classification algorithms for detection of fracture location in dissimilar friction stir welded joints by Akshansh Mishra, Apoorv Vats

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