activity
20152021
most citedA novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image

136 citations · 240 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2021★ 1 cited

Densely Deformable Efficient Salient Object Detection Network

Tanveer Hussain, Saeed Anwar, Amin Ullah +2

Salient Object Detection (SOD) domain using RGB-D data has lately emerged with some current models' adequately precise results. However, they have restrained generalization abiliti…

cs.LG2019★ 1 cited

Detection of Myocardial Infarction Based on Novel Deep Transfer Learning Methods for Urban Healthcare in Smart Cities

Ahmed Alghamdi, Mohamed Hammad, Hassan Ugail +4

. In this paper, an effective computer-aided diagnosis (CAD) system is presented to detect MI signals using the convolution neural network (CNN) for urban healthcare in smart citie…

cs.MM2016★ 13 cited

A New Image Steganographic Technique using Pattern based Bits Shuffling and Magic LSB for Grayscale Images

Khan Muhammad, Jamil Ahmad, Haleem Farman +1

Image Steganography is a growing research area of information security where secret information is embedded in innocent-looking public communication. This paper proposes a novel cr…

cs.MM2015★ 2 cited

Steganography: A Secure way for Transmission in Wireless Sensor Networks

Khan Muhammad

Addressing the security concerns in wireless sensor networks (WSN) is a challenging task, which has attracted the attention of many researchers from the last few decades. Researche…

cs.MM2015★ 28 cited

Secure Image Steganography using Cryptography and Image Transposition

Khan Muhammad, Jamil Ahmad, Muhammad Sajjad +1

Information security is one of the most challenging problems in today's technological world. In order to secure the transmission of secret data over the public network (Internet),…

cs.MM2015★ 11 cited

Ontology-based Secure Retrieval of Semantically Significant Visual Contents

Khan Muhammad, Irfan Mehmood, Mi Young Lee +2

Image classification is an enthusiastic research field where large amount of image data is classified into various classes based on their visual contents. Researchers have presente…