Pedestrian-Crossing Detection Enhanced by CyclicGAN-Based Loop Learning and Automatic Labeling by Kuan-Chieh Wang, Chao-Li Meng, Chyi-Ren Dow, Bonnie Lu

“…The scarcity and difficulty of collecting data under such complex conditions pose significant challenges to the development of accurate detection systems. …”
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Developing an innovative lung cancer detection model for accurate diagnosis in AI healthcare systems by Wang Jian, Amin Ul Haq, Noman Afzal, Shakir Khan, Hadeel Alsolai, Sultan M. Alanazi, Abu Taha Zamani

“…The model (CNN-GRU) was validated using LC data using the holdout validation technique. Data augmentation techniques such as rotation, and brightness were used to enlarge the data set size for effective training of the model. …”
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Evaluating the technical and economic aspects of thermal performance of extensive green roofs: A GIS-based case study in the urban setting of Na- dor, Morocco by Rachid Lambarki, Elmostafa Achbab, Mehdi Maanan, Hassan Rhinane

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Deep learning-based occlusion-aware face mask detection for airborne disease control by Teshome Ayechiluhem Yalew, Sosina M. Gashaw, Aleka Melese Ayalew, Mourad Oussalah

“…In this study, we collect data from public and local sources to develop an occlusion-aware face mask detection model. …”
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Designing a Smartphone Application for Detection of Oral Bite Force Using Artificial Intelligence by Jinxia Gao, Huazheng Zhou, Longjun Liu

“…Additionally, this program application provided feedback by detecting collected data and utilizing various output modes based on pre-set threshold values to prompt patients for self-correction, thereby achieving biofeedback regulation. …”
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Optimising Solar Power Plant Reliability Using Neural Networks for Fault Detection and Diagnosis by Mohammed Bouzidi, Abdelfatah Nasri, Omar Ouledali, Messaoud Hamouda

“…Research advocates for the integration of artificial neural networks with other machine learning methodologies, such as support vector machines, to improve fault prediction precision. Augmenting the data set by integrating data from various PV stations in different regions may improve the adaptability of the model to different environmental conditions. …”
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Cardiovascular wellness in low-resource settings: A mobile app-based risk prediction study among fuel filling station employees in Puducherry district by Divyabharathy Ramadass, Jyothi Vasudevan, Madonna J. Dsouza, Baalaji Subramanian

“…The burden of NCDs puts a strain on the healthcare system, requiring an increased focus on preventive measures, early detection, and management of chronic conditions. Adopting a risk-based approach to cardiovascular diseases (CVDs) in resource-poor settings offers several economic and social advantages. …”
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DETECTION OF MYOCARDIAL VIABILITY IN ISСHAEMIC DAMAGE USING MAGNETIC RESONANCE AND EMISSION TOMOGRAPHY by V. Yu. Ussov, A. A. Bogunetsky

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Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models by Rijvan Beg, R. K. Pateriya, Deepak Singh Tomar

“…In the evolving cyber threat landscape, one of the most visible and pernicious challenges is malware activity detection and analysis. Traditional detection and analysis methods face threats of data high-dimensionality, lack of strength against adversarial attacks, and non-efficient use of unlabeled data samples. …”
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Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

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Weirdnodes: centrality based anomaly detection on temporal networks for the anti-financial crime domain by Salvatore Vilella, Arthur Capozzi, Marco Fornasiero, Dario Moncalvo, Valeria Ricci, Silvia Ronchiadin, Giancarlo Ruffo

“…By providing a bird’s eye view of financial data, our approach mitigates the risk of overlooking complex behaviors that single-node or narrowly focused transactional analyses may fail to detect.…”
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Blending Static and Dynamic Analysis for Web Application Vulnerability Detection: Methodology and Case Study by Paulo Nunes, Jose Fonseca, Marco Vieira

“…In this paper, we blend SA and DA to simultaneously improve the detection and decrease the false alarms. Our approach starts with SA to identify an initial set of potential vulnerabilities. …”
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Advancing blood cell detection and classification: performance evaluation of modern deep learning models by Shilpa Choudhary, Sandeep Kumar, Pammi Sri Siddhaarth, Guntu Charitasri, Monali Gulhane, Nitin Rakesh, Feslin Anish Mon, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

“…Additionally, an annotated blood cell data set was generated for this study. A diverse set of blood cell images with fine-grained annotations is contained in this dataset to make it useful for deep learning models training and evaluation. …”
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Automatic Detection and Calculation of Mining Subsidence in Large-Scale Interferograms With Transformer-CNN Model by Hongdong Fan, Jialin Xin, Tao Lin, Jun Wang

“…Validation experiments utilizing Sentinel-1, ALOS-2, and LT-1 satellite data demonstrated that: 1) RAUNet enables precise detection of subsidence zones followed by calculation applied exclusively to the interferogram tiles within those zones, significantly improving data-processing efficiency and more intuitively revealing surface deformation in mining areas; 2) RAUNet can adapt to the differences between C-band and L-band data, yielding superior accuracy compared with traditional methods across multiple interferometric pairs. …”
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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

“…In this article, we conduct a comprehensive review of articles from 2013 to 2023, exploring how these technologies are applied in fire detection and extinguishing. We delve into modern techniques enabling real-time analysis of the visual data captured by cameras or satellites, facilitating the detection of smoke, flames, and other fire-related cues. …”
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Use of endoanal ultrasound in detecting obstetric anal sphincter injury immediately after birth by Malin Huber, Charlotta Larsson, Mathilda Harrysson, Karin Strigård, Jan‐P. Lehmann, Pär Nordin, Katarina Tunón

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The Relevance of Osteoscintigraphy Technique in Early Detection of Bone Metastatic Lesions: a Systematic Review by E. A. Litvinenko, I. V. Burova

“…Objective: to summarize data on the diagnostic effectiveness of osteoscintigraphy (OSG), as well as to conduct a comparative analysis of various diagnostic methods in bone metastases detection. …”
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Physiological signal-based mental stress detection using hybrid deep learning models by Nandini Modi, Yogesh Kumar, Kapil Mehta, Neelam Chaplot

“…In this study, a hybrid deep learning model combining Convolution neural network (CNN) with Multilayer perceptron (MLP) is proposed to classify mental stress levels based on physiological signal data. The dataset comprises a diverse set of physiological biomarkers correlated with different mental states. …”
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Detection of Diffusion Interlayers in Dissimilar Welded Joints in Processing Pipelines by Acoustic Emission Method by Vera Barat, Artem Marchenkov, Vladimir Bardakov, Dmitrij Arzumanyan, Sergey Ushanov, Marina Karpova, Egor Lepsheev, Sergey Elizarov

“…When using a backpropagation neural network, a percentage of correct classification of more than 90% was obtained for a data set in which the signal-to-noise ratio was less than (−5 dB) in 90% of cases.…”
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Current state and prospects of implementation of data standardization in the health care system of Ukraine (literature review) by D.Ye. Kaduk, T.M. Aleksandrova, P.S. Talapova, I.B. Agieieva, M.M. Ved, M.O. Trofymenko, M.R. Kolesnyk, T.S. Nesmiian

“…One of the most powerful and modern ways to improve the medical health care system is to introduce the standardization of the format and content of medical data. Quality implementation of the standardization program is a leading factor in the improvement of the quality of medical services, such as: early detection of diseases and emergencies, setting new therapeutic goals, improving the quality of clinical trials, improving of assessment of the quality of medical services and work of the doctors and nursing staff, improving the efficiency of health care programs, improving the safety of use of medical devices, forecasting medical consequences, reducing administrative costs, integrating artificial intelligence into the healthcare system, etc.…”
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