Combining CNN features with voting classifiers for optimizing performance of brain tumor classification
Simple Summary This study presents a hybrid model for brain tumor detection. Contrary to
manual featur extraction, features extracted from a convolutional neural network are used to …
manual featur extraction, features extracted from a convolutional neural network are used to …
Skin lesion classification on dermatoscopic images using effective data augmentation and pre-trained deep learning approach
F Bozkurt - Multimedia Tools and Applications, 2023 - Springer
Skin cancer is a severe disease that is common and causes death if left untreated. When
skin cancer is detected early through dermatoscopic imaging, the possibility of definitive …
skin cancer is detected early through dermatoscopic imaging, the possibility of definitive …
Skin Cancer Detection and Classification Using Neural Network Algorithms: A Systematic Review
In recent years, there has been growing interest in the use of computer-assisted technology
for early detection of skin cancer through the analysis of dermatoscopic images. However …
for early detection of skin cancer through the analysis of dermatoscopic images. However …
[PDF][PDF] Automatic identification of ivorian plants from herbarium specimens using deep learning
Plant identification is most often based on visual observations by botanists and systematists.
Deep learning has become a tool that provides an alternative to automatic plant …
Deep learning has become a tool that provides an alternative to automatic plant …
A novel approach for breast cancer detection using optimized ensemble learning framework and XAI
Breast cancer (BC) is a common and highly lethal ailment. It stands as the second leading
contributor to cancer-related deaths in women worldwide. The timely identification of this …
contributor to cancer-related deaths in women worldwide. The timely identification of this …
Multi-class skin lesion classification using prism-and segmentation-based fractal signatures
JA Camacho-Gutiérrez, S Solorza-Calderón… - Expert Systems with …, 2022 - Elsevier
Today, due to technological advances, specialists can count on a wide range of computer-
aided diagnostic applications. However, there are still significant challenges to overcome …
aided diagnostic applications. However, there are still significant challenges to overcome …
White blood cells classification using multi-fold pre-processing and optimized CNN model
White blood cells (WBCs) play a vital role in immune responses against infections and
foreign agents. Different WBC types exist, and anomalies within them can indicate diseases …
foreign agents. Different WBC types exist, and anomalies within them can indicate diseases …
Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects
UA Lyakhova, PA Lyakhov - Computers in Biology and Medicine, 2024 - Elsevier
In recent years, there has been a significant improvement in the accuracy of the
classification of pigmented skin lesions using artificial intelligence algorithms. Intelligent …
classification of pigmented skin lesions using artificial intelligence algorithms. Intelligent …
Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network
Blood cancer has emerged as a growing concern over the past decade, necessitating early
diagnosis for timely and effective treatment. The present diagnostic method, which involves …
diagnosis for timely and effective treatment. The present diagnostic method, which involves …
A hybrid feature fusion strategy for early fusion and majority voting for late fusion towards melanocytic skin lesion detection
A computer‐aided‐diagnostic system for diagnosing melanoma often uses distinct kinds of
features for characterizing the lesions. Extracting distinct features from melanocytic images …
features for characterizing the lesions. Extracting distinct features from melanocytic images …