Muhammad Younus Javed

TL;DR: It has been concluded that the Blowfish is the best performing algorithm among the algorithms chosen for implementation, and their performance is compared by encrypting input files of varying contents and sizes, on different Hardware platforms.

TL;DR: The proposed hybrid method for detection and classification of diseases in citrus plants outperforms the existing methods and achieves 97% classification accuracy on citrus disease image gallery dataset, 89% on combined dataset and 90.4% on the authors' local dataset.

TL;DR: This research proposes a hybrid strategy for efficient classification of human activities from a given video sequence by integrating four major steps: segment the moving objects by fusing novel uniform segmentation and expectation maximization, extract a new set of fused features using local binary patterns with histogram oriented gradient and Harlick features, and feature classification using multi-class support vector machine.

TL;DR: Simulation results reveal that the proposed method performs exceptionally better compared with existing works, and different performance measures are considered.

TL;DR: The overall results show that the performance of the proposed system for skin lesion classification through transfer learning based deep neural network (DCNN) features extraction and kurtosis controlled principle component (KcPCA) based optimal features selection is reliable as compared to existing techniques.