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[Retracted] Deep Neural Networks for Medical Image Segmentation
P Malhotra, S Gupta, D Koundal… - Journal of …, 2022 - Wiley Online Library
Image segmentation is a branch of digital image processing which has numerous
applications in the field of analysis of images, augmented reality, machine vision, and many …
applications in the field of analysis of images, augmented reality, machine vision, and many …
Tumor type detection in brain MR images of the deep model developed using hypercolumn technique, attention modules, and residual blocks
Brain cancer is a disease caused by the growth of abnormal aggressive cells in the brain
outside of normal cells. Symptoms and diagnosis of brain cancer cases are producing more …
outside of normal cells. Symptoms and diagnosis of brain cancer cases are producing more …
Abnormality detection and intelligent severity assessment of human chest computed tomography scans using deep learning: a case study on SARS-COV-2 …
Different respiratory infections cause abnormal symptoms in lung parenchyma that show in
chest computed tomography. Since December 2019, the SARS-COV-2 virus, which is the …
chest computed tomography. Since December 2019, the SARS-COV-2 virus, which is the …
[HTML][HTML] A novel extension of the TOPSIS method adapted for the use of single-valued neutrosophic sets and hamming distance for e-commerce development …
Neutrosophic sets have been recognized as an effective approach in solving complex
decision-making (DM) problems, mainly when such problems are related to uncertainties, as …
decision-making (DM) problems, mainly when such problems are related to uncertainties, as …
A new method for image processing using generalized linguistic neutrosophic cubic aggregation operator
Image processing is a technique of scrutinizing an image and extricating important
information. Indecisive situations are generally undergone when the picture processes with …
information. Indecisive situations are generally undergone when the picture processes with …
Neutrosophic set based local binary pattern for texture classification
N Alpaslan - Expert Systems with Applications, 2022 - Elsevier
This paper presents novel neutrosophic set-based Completed Local Binary Pattern (CLBP)
hybrid methods. These methods first transform the input image into a neutrosophic domain …
hybrid methods. These methods first transform the input image into a neutrosophic domain …
Map** fracture complexity of fractured shale in laboratory: three-dimensional reconstruction from serial-section images
The intrinsic anisotropy of sedimentary rocks such as shale, together with the presence of
natural fractures and bedding planes, make it possible for hydraulic fracturing to generate …
natural fractures and bedding planes, make it possible for hydraulic fracturing to generate …
Neutrosophic logic theory and applications
E AboElHamd¹, HMSM Saleh… - Neutrosophic Sets and …, 2021 - books.google.com
Neutrosophic logic is a very powerful and effective concept. It has different application areas
due to its ability to capture the stochasticity in many complex real-life use cases. This paper …
due to its ability to capture the stochasticity in many complex real-life use cases. This paper …
Segmentation of medical image using novel dilated ghost deep learning model
Image segmentation and computer vision are becoming more important in computer‐aided
design. A computer algorithm extracts image borders, colours, and textures. It also depletes …
design. A computer algorithm extracts image borders, colours, and textures. It also depletes …
[HTML][HTML] Automated defect analysis of additively fabricated metallic parts using deep convolutional neural networks
Laser powder bed fusion (LPBF)-based additive manufacturing (AM) has the flexibility in
fabricating parts with complex geometries. However, using non-optimized processing …
fabricating parts with complex geometries. However, using non-optimized processing …