Results 1 to 10 of about 62,767 (259)
Hyperparameter Optimization of Ensemble Models for Spam Email Detection
Applied Sciences (Switzerland), 2023 Unsolicited emails, popularly referred to as spam, have remained one of the biggest threats to cybersecurity globally. More than half of the emails sent in 2021 were spam, resulting in huge financial losses.
David Oyewola +1 more
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Hyperparameter Optimization of Convolutional Neural Networks for Robust Tumor Image Classification [PDF]
DiagnosticsBackground/Objectives: The human brain is responsible for controlling various physiological functions, and hence, the presence of tumors in the brain is a major concern in the medical field.
Syed Muddusir Hussain +4 more
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Improving the Robustness and Quality of Biomedical CNN Models through Adaptive Hyperparameter Tuning
Applied Sciences (Switzerland), 2022 Deep learning is an obvious method for the detection of disease, analyzing medical images and many researchers have looked into it. However, the performance of deep learning algorithms is frequently influenced by hyperparameter selection, the question of
Saeed Iqbal +2 more
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EV-Planner: a machine learning approach to electric vehicle charging infrastructure planning [PDF]
Frontiers in Artificial IntelligenceElectric Vehicles (EVs) offer pathways to lower emissions and increased energy efficiency. However, a broad and equitable adoption of electric vehicles can only be realized with well-planned growth in public charging infrastructure. We propose EV-Planner,
Bharath Anand, Ananth Grama
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IEEE Access, 2023 Point clouds are generated by light imaging, detection and ranging (LIDAR) scanners or depth imaging cameras, which capture the geometry from the scanned objects with high accuracy. Unfortunately, these systems are unable to identify the semantics of the
Eike Barnefske, Harald Sternberg
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Remote Sensing, 2023 Spatial prediction of soil ammonia (NH3) plays an important role in monitoring climate warming and soil ecological health. However, traditional machine learning (ML) models do not consider optimal parameter selection and spatial autocorrelation. Here, we
Yingqiang Song +9 more
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Mathematics, 2023 (1) Background: sentiment analysis is a computational technique employed to discern individuals opinions, attitudes, emotions, and intentions concerning a subject by analyzing reviews.
Ewen Hokijuliandy +2 more
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Prediction of Vestibular Dysfunction by Applying Machine Learning Algorithms to Postural Instability
Frontiers in Neurology, 2020 Objective: To evaluate various machine learning algorithms in predicting peripheral vestibular dysfunction using the dataset of the center of pressure (COP) sway during foam posturography measured from patients with dizziness.Study Design: Retrospective ...
Teru Kamogashira +5 more
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Barekeng, 2023 The growth of news articles on the internet occurs in a short period with large amounts so necessary to be grouped into several categories for easy access. There is a method for grouping news articles, namely classification.
Dewi Retno Sari Saputro, Krisna Sidiq
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A hierarchical optimisation framework for pigmented lesion diagnosis
CAAI Transactions on Intelligence Technology, 2022 The study of training hyperparameters optimisation problems remains underexplored in skin lesion research. This is the first report of using hierarchical optimisation to improve computational effort in a four‐dimensional search space for the problem. The
Audrey Huong +3 more
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