Muhammad Sajjad

Norwegian University of Science and Technology

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Co-Authors

Sung Wook Baik

Sejong University

Khan Muhammad

Sungkyunkwan University

Irfan Mehmood

Zhejiang University

Amin Ullah

Oregon State University

Seungmin Rho

Sungkyul University

Jamil Ahmad

United Arab Emirates University

Faouzi Alaya Cheikh

Norwegian University of Science and Technology

Zahoor Jan

Islamia College University

Tanveer Hussain

Sejong University

Ali Shariq Imran

Norwegian University of Science and Technology

Cooperative Institutions

Sejong University

Islamia College University

The University of Agriculture, Peshawar

COMSATS University Islamabad

University of Agriculture Faisalabad

Abdul Wali Khan University Mardan

University of Engineering and Technology Lahore

National University of Sciences and Technology

ORCID

Norwegian University of Science and Technology

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Prioritization of brain MRI volumes using medical image perception model and tumor region segmentation

Computers in Biology and Medicine (2013)

Irfan Mehmood Naveed Ejaz Muhammad Sajjad Sung Wook Baik

Prioritization

Modality (human–computer interaction)

Brain tumor

Modalities

10.1016/j.compbiomed.2013.07.001

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Citations (51)

Let the deaf understand: Mainstreaming the marginalized in context with personalized digital media services and social needs

Irfan Mehmood Tanveer Hussain Ibrahim A. Hassan Seungmin Rho Muhammad Sajjad

This paper presents a pilot study for a personalized media service which aims at creating an intelligent, sentiment-aware, and language-independent access to large archives of audiovisual documents, providing equal services to both mainstream and marginalized users. The proposed multi-modal framework analyzes aural, visual, and human descriptions, integrating them into an automatic content analyzer. Firstly, text is extracted from the aural stream and mapped to American Sign Language (ASL), translating conventional video to content suitable for the deaf. Next, sentiment is estimated from text, aural, and visual contents using two deep convolutional neural networks (CNN), extracting discriminative features from each modality. This provides output predictions for two broad classes: positive and negative sentiments. Preliminary results indicate that the proposed approach is capable of accurately estimating the sentiment of multimedia contents, which is an important step for personalized and intelligent media services.

Modality (human–computer interaction)

Mainstream

Discriminative model

10.1109/icmew.2017.8026328

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Citations (5)

QuickLook: Movie summarization using scene-based leading characters with psychological cues fusion

Information Fusion (2021)

Ijaz Ul Haq Khan Muhammad Tanveer Hussain Javier Del Ser Muhammad Sajjad

Baseline (sea)

Theme (computing)

Film Industry

10.1016/j.inffus.2021.04.016

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Citations (11)

Multi-kernel based adaptive interpolation for image super-resolution. Multimedia Tools Appl: 1-23

Muhammad Sajjad Naveed Ejaz Sung Wook Baik

Kernel (algebra)

Interpolation

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Citations (2)

Dual-Level Security based Cyclic18 Steganographic Method and its Application for Secure Transmission of Keyframes during Wireless Capsule Endoscopy

Journal of Medical Systems (2016)

Khan Muhammad Muhammad Sajjad Sung Wook Baik

Scrambling

Secure transmission

10.1007/s10916-016-0473-x

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Citations (67)

Improved colorization and classification of intracranial tumor expanse in MRI images via hybrid scheme of Pix2Pix-cGANs and NASNet-large

Journal of King Saud University - Computer and Information Sciences (2022)

Mavra Mehmood Nasser Alshammari Saad Alanazi Asma Basharat Fahad Ahmad

Clinical image processing plays a significant role in healthcare systems and is a widely used methodology of the current era. The Intracranial tumor affects children and adults as it is the 10th most common form of tumor. Accurate tumor segmentation in the brain is complicated even though Intracranial tumor images are acquired properly. The tumor can be curable if its stage and form can be identified on time, and for this purpose, researchers have been developing sophisticated techniques and methods. An automatic detection, segmentation, colorization, and classification of tumor region are done to identify abnormalities in a medical image using T1-CE, an MRI dataset that assists in diagnosis. To assist the medical practitioners in visualizing tumor shape, size, and orientation; only the tumor region is colored in a greyscale image. Pix2Pix Conditional Generative Adversarial Neural Networks (Pix2Pix-cGANs) have generated MRI images with color tumor regions. In qualitative measures, we achieved the Structure Similarity Index (SSIM) average score of 0.92% and an average 28% Peak Signal to Noise Ratio (PSNR) value on generated images that outperform the existing techniques. Moreover, we achieved Classification Accuracy (CA) 88.5% and 92.4% quantitatively in pre and post colorization phases, respectively, with other measures using NASNet-Large.

Brain tumor

Similarity (geometry)

10.1016/j.jksuci.2022.05.015

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Citations (39)

Implementation of Asymmetric Potential Fields in Real Time Strategy Game

Muhammad Mansur-Ul-Islam Muhammad Sajjad

In eighties, the idea of using potential fields was first introduced in the field of the robotics. The purpose of using potential fields was to achieve the natural movement in robotics. Many researchers proceeded this idea to enhance their research. The idea of using potential fields was also introduced in real time strategy games for the better movement of objects. In this thesis we worked on the idea of using asymmetric potential fields in the game environment. The purpose of our study was to analyze the affect of asymmetric potential fields on unit’s formation and their movement in game environment. In this study performance of asymmetric potential fields was also compared with symmetric potential fields. By literature review the potential field and its usage in RTS games were studied. The methodology to implement the potential fields in RTS game was also identified in literature review. In experimental part the asymmetric potential fields implemented by using the methodology proposed by Hagelback and Johansson. By following that methodology asymmetric potential field was applied on StarCraft bot by using the BWAPI. Experiment was also designed to test the asymmetric potential field bot. Asymmetric potential field bot was tested on the two maps of StarCraft: Brood War game. On these two maps, bot implemented with asymmetric potential field and the bot implemented with symmetric potential field competed with four bots. Three bots were selected from StarCraft competition and one was built-in bot of this game. The results of these competition shows that asymmetric potential field bot has better performance than symmetric potential field bot. The results of experiments show that the performance of bot implemented with asymmetric potential fields was better than symmetric potential field on single unit type and two unit types. This study shows that with the help of asymmetric potential fields interesting unit formation can be formed in real time strategy games, which can give better result than symmetric potential fields.

Potential field

Potential game

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Citations (0)

Efficient visual attention driven framework for key frames extraction from hysteroscopy videos

Biomedical Signal Processing and Control (2016)

Khan Muhammad Muhammad Sajjad Mi Young Lee Sung Wook Baik

10.1016/j.bspc.2016.11.011

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Citations (47)

An Automated Approach for Analysing Students Feedback Using Sentiment Analysis Techniques