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Found 10 papers, 0 papers with code
Learning Style Identification Using Semi-Supervised Self-Taught Labeling
Education is a dynamic field that must be adaptable to sudden changes and disruptions caused by events like pandemics, war, and natural disasters related to climate change.
Knowledge Management Systems Requirements Specifications
In recent years, Knowledge Management Systems (KMS) have drawn remarkable attention.
Spatio-Temporal Segmentation in 3D Echocardiographic Sequences using Fractional Brownian Motion
An important aspect for an improved cardiac functional analysis is the accurate segmentation of the left ventricle (LV).
Heterogeneous tissue characterization using ultrasound: a comparison of fractal analysis backscatter models on liver tumors
Performance was assessed based on 608 cross-sectional clinical ultrasound RF images of liver tumors (230 and 378 demonstrating respondent and non-respondent cases, respectively).
Multiscale Nakagami parametric imaging for improved liver tumor localization
The varying size kernel integrates the goodness-of-fit of the backscattering distribution parameters at multiple scales for more stable parameter estimation.
A Gabor Filter Texture Analysis Approach for Histopathological Brain Tumor Subtype Discrimination
The highest classification accuracy of 95% was reported when combining the Gabor filters energy and the meningioma subimage fractal signature as a feature vector without performing any prior cell nuceli segmentation.
A fractal dimension based optimal wavelet packet analysis technique for classification of meningioma brain tumours
With the heterogeneous nature of tissue texture, using a single resolution approach for optimum classification might not suffice.
Supervised Texture Segmentation: A Comparative Study
This paper aims to compare between four different types of feature extraction approaches in terms of texture segmentation.
Texture measures combination for improved meningioma classification of histopathological images
Providing an improved technique which can assist pathologists in correctly classifying meningioma tumours with a significant accuracy is our main objective.
A Multiresolution Clinical Decision Support System Based on Fractal Model Design for Classification of Histological Brain Tumours
A clinical decision support system that exploits the subband textural fractal characteristics for best bases selection of meningioma brain histopathological image classification is proposed.
