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using algorithm » cosine algorithm (Expand Search)
element based » event based (Expand Search)
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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…The collection of digital images for monitoring underwater habitats, such as seagrass meadows, has increased significantly as recent progress in imaging technology has made it easier to collect high-resolution data. The increase in imagery data has in turn created a demand for automated detection and classification using deep neural network-based techniques. …”
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806
Decision-level fusion for single-view gait recognition with various carrying and clothing conditions
Published 2017“…Gait samples are fed into the MPCA and MPCALDA algorithms using a novel tensor-based form of the gait images. …”
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807
A Machine Learning Approach to Predicting Diabetes Complications
Published 2021Get full text
doctoralThesis -
808
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…The pre-trained DenseNet201 network is used for CNN feature extraction from each task-specific handwritten image data. …”
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Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic
Published 2020“…The data obtained from the study were analyzed by using the partial least squares structural equation modeling (PLS-SEM) and machine learning algorithms. …”
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Artificial intelligence models for predicting the mode of delivery in maternal care
Published 2025“…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…The pre-trained DenseNet201 network is used for CNN feature extraction from each task-specific handwritten image data. …”
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Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review
Published 2022“…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”
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Combinatorial method for bandwidth selection in wind speed kernel density estimation
Published 2019“…This goal calls for devising probabilistic models with adaptive algorithms that accurately fit wind speed distributions. …”
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LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications
Published 2024Get full text
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Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models
Published 2024“…Dialect Speech Sentiment Analysis is an evolutional field where machine learning algorithms are utilized to detect emotions in spoken language. …”
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Legal and Ethical Considerations of Artificial Intelligence for Residents in Post-Acute and Long-Term Care
Published 2024“…Third, privacy rules concerning data use may undermine developers’ ability to train accurate AI systems, limiting their usefulness in PA-LTC contexts. …”
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Accelerating Blockchain Transaction Verification With Parallel Computing
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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits
Published 2022“…This procedure entailed using our large-scale dataset to refine toxicity triggers' definition and build a trigger detection dataset using 991,806 conversation threads from the top 100 communities on Reddit. …”
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FoGMatch
Published 2019“…To address this problem, we propose in this paper a multi-criteria intelligent IoT scheduling approach in fog computing environments using matching game theory. Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …”
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masterThesis