This paper introduces an innovative approach to Content-Based image Retrieval (CBIR) that leverages Harris Hawks Optimization (HHO) to improve feature selection and retrieval accuracy. CBIR systems are increasingly im...
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Medical image segmentation is a plan that has a lot of potential. The achievement of automated picture segmentation makes it simple to gather biomedical and anatomical information. In terms of the subject, more study ...
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para>Defects in pipeline welds are fatal for pipelines, considering that weld negatives need to be electronically preserved due to high preservation costs, easy damage, etc., and that most of the weld defects are j...
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The proceedings contain 134 papers. The topics discussed include: an adaptive storage switching algorithm for fault-tolerant network attached storage systems;Covid-19 prediction using machine learning algorithms;energ...
ISBN:
(纸本)9798350387933
The proceedings contain 134 papers. The topics discussed include: an adaptive storage switching algorithm for fault-tolerant network attached storage systems;Covid-19 prediction using machine learning algorithms;energy management of hybrid electric vehicles using cascaded fuzzy logic controller;dynamic lane management with IoT for real-time lane configuration and traffic flow;a closer look at sclera: emerging trends in biometric security;cognitive vision companion: an ai-enhanced support system for the visually impaired;advances in medical imageprocessing for liver tumor recognition: a comprehensive survey;a gradient boosting algorithm to predict energy consumption for home applications;and review on text classification using improved deep learning models.
This paper reviews modern approaches for cell detection and segmentation in medical images aimed at determining antinuclear factors. Articles focused on the use of intelligent technologies for antinuclear factor deter...
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作者：
Menconero, SofiaDepartment of History
Representation and Restoration of Architecture Sapienza University of Rome Piazza Borghese 9 Rome00186 Italy
Piranesi printed the 16 etchings of the Carceri d’invenzione in 1761. This version, which is more widespread and better known, derives from the reworking of matrices that the Venetian engraver produced in 1749–50. T...
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The computer aided diagnosis systems from radiological images has been of interest to researchers mostly for detection of bone fracture or dislocation. The accuracy highly depends on bone segmentation. Any improvement...
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ISBN:
(数字)9788362065424
ISBN:
(纸本)9788362065424
The computer aided diagnosis systems from radiological images has been of interest to researchers mostly for detection of bone fracture or dislocation. The accuracy highly depends on bone segmentation. Any improvement of such systems, particularly for noisy X-ray images, is very valuable. Classical image segmentation depending on image homogeneity are time consuming and require pixel-wise labelling. On the other hand, saliency map based approaches fail to detect the region around the fracture or segment the dislocated bones. In our research we have used transfer learning to train the faster regional convolutional neural network (FCNN) alongside distance regularized level set evolution (DRLSE) to have accurate bone segmentation without any pixel-wise labelling enabling segmentation of the region around the fracture and dislocated bones. We applied the proposed method to a number of hand X-ray images and achieved accuracy values of 95% and average precision-recall of 0.96.
This paper presents a method based on the principle of harmonic /rotating coils, used for the rapid and complete characterization of the magnetic field created in the aperture of the electromagnetic particle accelerat...
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Communicating online without fearing third-party interventions is becoming a challenge in the modern world. Especially the sectors like the military, and government organizations or private companies sharing sensitive...
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Surface water resource identification is one of the main techniques used in remote sensing image analysis. This is necessary to stop calamities like floods and droughts. Feature selection based on prior information an...
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