Face mask detection using deep convolutional neural network and multi-stage image processing
Face mask detection has several applications including real-time surveillance, biometrics,
etc. Face mask detection is also useful for surveillance of the public to ensure face mask …
etc. Face mask detection is also useful for surveillance of the public to ensure face mask …
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 …
Improving prediction of cervical cancer using knn imputed smote features and multi-model ensemble learning approach
H Karamti, R Alharthi, AA Anizi, RM Alhebshi… - Cancers, 2023 - mdpi.com
Simple Summary This paper presents a cervical cancer detection approach where the KNN
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …
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 …
[HTML][HTML] Water-quality prediction based on H2O AutoML and explainable AI techniques
Rapid expansion of the world's population has negatively impacted the environment, notably
water quality. As a result, water-quality prediction has arisen as a hot issue during the last …
water quality. As a result, water-quality prediction has arisen as a hot issue during the last …
Temporal instability of motorcycle crash fatalities on local roadways: A random parameters approach with heterogeneity in means and variances
Motorcycle accidents can impede sustainable development due to the high fatality rate
associated with motorcycle riders, particularly in developing countries. Although there has …
associated with motorcycle riders, particularly in developing countries. Although there has …
Data-centric automated approach to predict autism spectrum disorder based on selective features and explainable artificial intelligence
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by notable
challenges in cognitive function, understanding language, recognizing objects, interacting …
challenges in cognitive function, understanding language, recognizing objects, interacting …
Enhancing prediction of brain tumor classification using images and numerical data features
Brain tumors, along with other diseases that harm the neurological system, are a significant
contributor to global mortality. Early diagnosis plays a crucial role in effectively treating brain …
contributor to global mortality. Early diagnosis plays a crucial role in effectively treating brain …
Improving prediction of cervical cancer using KNN imputer and multi-model ensemble learning
T Aljrees - Plos one, 2024 - journals.plos.org
Cervical cancer is a leading cause of women's mortality, emphasizing the need for early
diagnosis and effective treatment. In line with the imperative of early intervention, the …
diagnosis and effective treatment. In line with the imperative of early intervention, the …
Role of convolutional features and machine learning for predicting student academic performance from MOODLE data
Predicting student performance automatically is of utmost importance, due to the substantial
volume of data within educational databases. Educational data mining (EDM) devises …
volume of data within educational databases. Educational data mining (EDM) devises …