Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare

S Maqsood, R Damaševičius - Neural networks, 2023 - Elsevier
Background: The idea of smart healthcare has gradually gained attention as a result of the
information technology industry's rapid development. Smart healthcare uses next-generation …

Importance of features selection, attributes selection, challenges and future directions for medical imaging data: a review

N Naheed, M Shaheen, SA Khan… - … in Engineering & …, 2020 - ingentaconnect.com
In the area of pattern recognition and machine learning, features play a key role in
prediction. The famous applications of features are medical imaging, image classification …

Human action recognition using fusion of multiview and deep features: an application to video surveillance

MA Khan, K Javed, SA Khan, T Saba, U Habib… - Multimedia tools and …, 2024 - Springer
Abstract Human Action Recognition (HAR) has become one of the most active research area
in the domain of artificial intelligence, due to various applications such as video surveillance …

Brain tumor detection and classification: A framework of marker‐based watershed algorithm and multilevel priority features selection

MA Khan, IU Lali, A Rehman, M Ishaq… - Microscopy research …, 2019 - Wiley Online Library
Brain tumor identification using magnetic resonance images (MRI) is an important research
domain in the field of medical imaging. Use of computerized techniques helps the doctors for …

Hand-crafted and deep convolutional neural network features fusion and selection strategy: an application to intelligent human action recognition

MA Khan, M Sharif, T Akram, M Raza, T Saba… - Applied Soft …, 2020 - Elsevier
Human action recognition (HAR) has gained much attention in the last few years due to its
enormous applications including human activity monitoring, robotics, visual surveillance, to …

Computer-aided gastrointestinal diseases analysis from wireless capsule endoscopy: a framework of best features selection

MA Khan, S Kadry, M Alhaisoni, Y Nam, Y Zhang… - IEEE …, 2020 - ieeexplore.ieee.org
The continuous improvements in the area of medical imaging, makes the patient monitoring
a crucial concern. The internet of things (IoT) embedded in a medical technologies to collect …

Pearson correlation-based feature selection for document classification using balanced training

IM Nasir, MA Khan, M Yasmin, JH Shah, M Gabryel… - Sensors, 2020 - mdpi.com
Documents are stored in a digital form across several organizations. Printing this amount of
data and placing it into folders instead of storing digitally is against the practical, economical …

An in-depth evaluation of deep learning-enabled adaptive approaches for detecting obstacles using sensor-fused data in autonomous vehicles

A Thakur, SK Mishra - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
This paper delivers an exhaustive analysis of the fusion of multi-sensor technologies,
including traditional sensors such as cameras, Light Detection and Ranging (LiDAR), Radio …

Multi-model deep neural network based features extraction and optimal selection approach for skin lesion classification

MA Khan, MY Javed, M Sharif, T Saba… - … on computer and …, 2019 - ieeexplore.ieee.org
Melanoma skin cancer is one of the most deadly forms of cancer which are responsible for
thousands of deaths. The manual process of melanoma diagnosis is a time taking and …

Skin lesion segmentation and classification: A unified framework of deep neural network features fusion and selection

MA Khan, MI Sharif, M Raza, A Anjum, T Saba… - Expert …, 2022 - Wiley Online Library
Automated skin lesion diagnosis from dermoscopic images is a difficult process due to
several notable problems such as artefacts (hairs), irregularity, lesion shape, and irrelevant …