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Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…In this paper, we present a twophase technique to classify images of lesions into benign or malignant. The first phase consists of an image processing-based method that extracts the Asymmetry, Border Irregularity, Color Variation and Diameter of a given mole. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…<p dir="ltr">In this paper, we propose a novel approach to solve nonlinear stress analysis problems in shell structures using an image processing technique. In general, such problems in design optimisation or virtual reality applications must be solved repetitively in a short period using direct methods such as nonlinear finite element analysis. …”
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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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Automatic image quality evaluation in digital radiography using for‐processing and for‐presentation images
Published 2024“…<h3>Purpose</h3><p dir="ltr">To investigate the impact of digital image post‐processing algorithms on various image quality (IQ) metrics of radiographic images under different exposure conditions.…”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…The feature fusion approach substantially improved the classification accuracy, with the SVM trained on fused features from the task specific-data achieving an accuracy of 97.3%. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…The feature fusion approach substantially improved the classification accuracy, with the SVM trained on fused features from the task specific-data achieving an accuracy of 97.3%. …”
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A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net
Published 2023“…Although, there are dedicated audio processing DNNs, yet, many recent models of AE have utilized U-Net: a DNN based on Convolutional Neural Network (CNN), fundamentally developed for image segmentation. …”
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The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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AI-Aided Robotic Wide-Range Water Quality Monitoring System
Published 2024Subjects: Get full text
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Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review
Published 2022“…It also summarizes the problems solved in image processing by DE and its variants.…”
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