Cargando…
A Novel and Effective Brain Tumor Classification Model Using Deep Feature Fusion and Famous Machine Learning Classifiers
Brain tumors are difficult to treat and cause substantial fatalities worldwide. Medical professionals visually analyze the images and mark out the tumor regions to identify brain tumors, which is time-consuming and prone to error. Researchers have proposed automated methods in recent years to detect...
Autores principales: | Kibriya, Hareem, Amin, Rashid, Alshehri, Asma Hassan, Masood, Momina, Alshamrani, Sultan S., Alshehri, Abdullah |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976620/ https://www.ncbi.nlm.nih.gov/pubmed/35378808 http://dx.doi.org/10.1155/2022/7897669 |
Ejemplares similares
-
A Novel Approach for Brain Tumor Classification Using an Ensemble of Deep and Hand-Crafted Features
por: Kibriya, Hareem, et al.
Publicado: (2023) -
Digital Forensics for Malware Classification: An Approach for Binary Code to Pixel Vector Transition
por: Naeem, Muhammad Rehan, et al.
Publicado: (2022) -
Deep fake detection and classification using error-level analysis and deep learning
por: Rafique, Rimsha, et al.
Publicado: (2023) -
A residual network-based framework for COVID-19 detection from CXR images
por: Kibriya, Hareem, et al.
Publicado: (2022) -
Osteo-NeT: An Automated System for Predicting Knee Osteoarthritis from X-ray Images Using Transfer-Learning-Based Neural Networks Approach
por: Alshamrani, Hassan A., et al.
Publicado: (2023)