Leveraging Deep Pre-trained Networks for Advanced Skin Lesion Classification for Human Monkeypox Detection
Journal Title: International Journal of Experimental Research and Review - Year 2025, Vol 47, Issue 1
Abstract
In response to recent human monkeypox outbreaks, the imperative of swiftly identifying and isolating infected individuals to curb transmission underscores the significance of innovative solutions. This study introduces an Android mobile application harnessing deep learning capabilities to address this urgent need. Developed using Java within Android Studio and Android SDK 12, the application leverages the device's camera via the Camera 2 API for real-time image capture. The captured video images are processed by a deep convolutional neural network (CNN) embedded within the device. Training the CNN involved utilizing a dataset containing skin lesion images from monkeypox-infected individuals and other skin conditions, employing a deep transfer learning methodology. The training and testing phases were executed using Matlab, with the selected network further trained using TensorFlow and adapted into a TensorFlow Lite model for mobile deployment. Successful testing on various devices yielded average inference times of 197 ms, 91 ms and 138 ms, affirming the application's efficiency. Facilitating swift preliminary diagnosis, the application empowers individuals with skin lesions to seek prompt medical attention, potentially curtailing disease transmission. Notably, the system exhibits a commendable 91.11% accuracy in classifying images, indicating its reliability. Moreover, its adaptable architecture suggests broader utility for training in diagnosing diverse skin diseases, reflecting a promising avenue for future healthcare innovations.
Authors and Affiliations
Madhur Nagrath, Poonam Chaudhary, Meghna Sharma
Keywords
Related Articles
- EP ID EP765350
- DOI 10.52756/ijerr.2025.v47.012
- Views 11
- Downloads 0
Performance Analysis of KNN, Naïve Bayes, and Extreme Learning Machine Techniques on EEG Signals for Detection of Parkinson's Disease
The application of bio-potentials for diagnosing neurological disorders has become highly effective nowadays. This work focuses on using Electroencephalogram (EEG) to detect Parkinson's disease (PD), a significant neurol...
Exploring Consumer Preferences and Behaviour Toward Digital Payment Gateways in India
This study explores consumer behaviour and preferences towards digital payment gateways in India, focusing on the factors that drive consumer choices and satisfaction. A structured survey with a stratified random sample...
Flood hazard and damage assessment in former Jalpaiguri district of West Bengal, India
Flood is the most common and natural phenomena of any flood prone region and damage is also very common event related to flood hazard of any magnitude. Impact of flood in any particular area is always concerned with the...
Evaluation of different bivoltine pure silkworm breed for cocoon and associated parameters under Uttar Dinajpur agro climatic conditions west Bengal, India
Four pure bivoltine silkworm breeds SK6, SK7, BCon1 and BCon4 were evaluated under Uttar Dinajpur agro climatic (Raiganj) conditions West Bengal in two different crop seasons along with their mean performance. The cocoon...
Isozyme profiling of Antioxidant Enzyme in Macrotyloma uniflorum
The current climate change and pollution scenario has invariably increased the abiotic stress of salinity, heavy metals, and temperature on plants. Abiotic stress impacts the plant's defense system, impacting the crop's...