Search alternatives:
group classification » _ classification (Expand Search), image classification (Expand Search), text classification (Expand Search)
model optimization » level optimization (Expand Search), motor optimization (Expand Search), monkey optimizations (Expand Search)
binary a » binary rat (Expand Search)
group classification » _ classification (Expand Search), image classification (Expand Search), text classification (Expand Search)
model optimization » level optimization (Expand Search), motor optimization (Expand Search), monkey optimizations (Expand Search)
binary a » binary rat (Expand Search)
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024“…<p dir="ltr">Glaucoma is defined as progressive optic neuropathy that damages the structural appearance of the optic nerve head and is characterized by permanent blindness. For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
Published 2025Get full text
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An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
Published 2022“…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
Published 2023“…The VGG19 network yielded a health condition classification accuracy of 100% with an RMSE of 0.33% and a maximum classification error score of 0.87 %.…”
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Get full text
Get full text
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Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes
Published 2025“…In the first stage, we performed binary classification, grouping SAH severity into “Good Outcome” (class 0), which includes MRS levels 0, 1, 2, and 3, and “Poor Outcome” (class 1), encompassing levels 4, 5, and 6. …”