Muhammad Sharif
Muhammad Sharif
Professor, Department of Computer Science, COMSATS University Islamabad, Wah Campus
Verified email at - Homepage
Cited by
Cited by
An automated detection and classification of citrus plant diseases using image processing techniques: A review
Z Iqbal, MA Khan, M Sharif, JH Shah, MH ur Rehman, K Javed
Computers and electronics in agriculture 153, 12-32, 2018
Detection and classification of citrus diseases in agriculture based on optimized weighted segmentation and feature selection
M Sharif, MA Khan, Z Iqbal, MF Azam, MIU Lali, MY Javed
Computers and electronics in agriculture 150, 220-234, 2018
A distinctive approach in brain tumor detection and classification using MRI
J Amin, M Sharif, M Yasmin, SL Fernandes
Pattern Recognition Letters 139, 118-127, 2020
Brain tumor detection using fusion of hand crafted and deep learning features
T Saba, AS Mohamed, M El-Affendi, J Amin, M Sharif
Cognitive Systems Research 59, 221-230, 2020
Big data analysis for brain tumor detection: Deep convolutional neural networks
J Amin, M Sharif, M Yasmin, SL Fernandes
Future Generation Computer Systems 87, 290-297, 2018
Internet of Things (IoT) operating systems support, networking technologies, applications, and challenges: A comparative review
F Javed, MK Afzal, M Sharif, BS Kim
IEEE Communications Surveys & Tutorials 20 (3), 2062-2100, 2018
Symptom based automated detection of citrus diseases using color histogram and textural descriptors
H Ali, MI Lali, MZ Nawaz, M Sharif, BA Saleem
Computers and Electronics in agriculture 138, 92-104, 2017
Brain tumor detection using statistical and machine learning method
J Amin, M Sharif, M Raza, T Saba, MA Anjum
Computer methods and programs in biomedicine 177, 69-79, 2019
CCDF: Automatic system for segmentation and recognition of fruit crops diseases based on correlation coefficient and deep CNN features
MA Khan, T Akram, M Sharif, M Awais, K Javed, H Ali, T Saba
Computers and electronics in agriculture 155, 220-236, 2018
A citrus fruits and leaves dataset for detection and classification of citrus diseases through machine learning
HT Rauf, BA Saleem, MIU Lali, MA Khan, M Sharif, SAC Bukhari
Data in brief 26, 104340, 2019
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, M Sharif, T Saba, S Zahoor, ...
Microscopy research and technique 82 (6), 909-922, 2019
An optimized method for segmentation and classification of apple diseases based on strong correlation and genetic algorithm based feature selection
MA Khan, MIU Lali, M Sharif, K Javed, K Aurangzeb, SI Haider, ...
IEEE Access 7, 46261-46277, 2019
A survey of password attacks and comparative analysis on methods for secure authentication
M Raza, M Iqbal, M Sharif, W Haider
World Applied Sciences Journal 19 (4), 439-444, 2012
A framework for offline signature verification system: Best features selection approach
M Sharif, MA Khan, M Faisal, M Yasmin, SL Fernandes
Pattern Recognition Letters 139, 50-59, 2020
A survey on medical image segmentation
S Masood, M Sharif, A Masood, M Yasmin, M Raza
Current Medical Imaging 11 (1), 3-14, 2015
An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor
M Sharif, J Amin, M Raza, M Yasmin, SC Satapathy
Pattern Recognition Letters 129, 150-157, 2020
An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach
M Nasir, M Attique Khan, M Sharif, IU Lali, T Saba, T Iqbal
Microscopy research and technique 81 (6), 528-543, 2018
A method for the detection and classification of diabetic retinopathy using structural predictors of bright lesions
J Amin, M Sharif, M Yasmin, H Ali, SL Fernandes
Journal of Computational Science 19, 153-164, 2017
Multi-model deep neural network based features extraction and optimal selection approach for skin lesion classification
MA Khan, MY Javed, M Sharif, T Saba, A Rehman
2019 international conference on computer and information sciences (ICCIS), 1-7, 2019
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, A Rehman
Applied Soft Computing 87, 105986, 2020
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