Publications

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Showing 21–40 of 46 publications

2020

Book ChaptersMedical ImagingMachine Learning & Deep Learning
Analysis of optical coherence tomography images using deep convolutional neural network for maculopathy grading.
Hassan, Taimur, Muhammad Usman Akram, and Imran Basit.
In Diabetes and Retinopathy, pp. 93-108. Elsevier, 2020.
Book ChaptersMachine Learning & Deep LearningInternet of Things
Multistage Deep Neural Network Framework for People Detection and Localization Using Fusion of Visible and Thermal Images.
Khalid, Bushra, Muhammad Usman Akram, and Asad Mansoor Khan.
In International Conference on Image and Signal Processing, pp. 138-147. Springer, Cham, 2020.
ISI Indexed / Impact Factor Journal PapersIF 4.42Medical ImagingMachine Learning & Deep Learning
Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression.
Raja, Hina, Taimur Hassan, Muhammad Usman Akram, and Naoufel Werghi.
IEEE Transactions on Biomedical Engineering (2020).
ISI Indexed / Impact Factor Journal PapersIF 3.697Medical ImagingMachine Learning & Deep Learning
Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis.
Raja, Hina, M. Usman Akram, Arslan Shaukat, Shoab Ahmed Khan, Norah Alghamdi, Sajid Gul Khawaja, and Noman Nazir.
Journal of Digital Imaging (2020): 1-15.
ISI Indexed / Impact Factor Journal PapersIF 3.275Biomedical Signal ProcessingMachine Learning & Deep Learning
CNN and LSTM-Based Emotion Charting Using Physiological Signals
Dar, M.N.; Akram, M.U.; Khawaja, S.G.; Pujari, A.N.
Sensors 2020, 20, 4551.
ISI Indexed / Impact Factor Journal PapersIF 4.217Medical ImagingMachine Learning & Deep Learning
RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology.
Hassan, Taimur, Muhammad Usman Akram, Naoufel Werghi, and Noman Nazir.
IEEE Journal of Biomedical and Health Informatics (2020).
Conference ProceedingsMedical ImagingMachine Learning & Deep Learning
Exploiting the Transferability of Deep Learning Systems Across Multi-modal Retinal Scans for Extracting Retinopathy Lesions.
Hassan, Taimur, Muhammad Usman Akram, and Naoufel Werghi.
In 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE), pp. 577-581. IEEE, 2020.

2019

Conference ProceedingsMachine Learning & Deep LearningData Analytics
A Machine Learning Technique to Classify LSST Observed Astronomical Objects Based on Photometric Data
Khan, A. M., Akram, M. U., Khawaja, S. G., & Khan, A. S. (2019, June).
In 2019 6th Swiss Conference on Data Science (SDS) (pp. 46-50). IEEE.
Conference ProceedingsMachine Learning & Deep Learning
Person detection by fusion of visible and thermal images using convolutional neural network
Khalid, B., Khan, A. M., Akram, M. U., & Batool, S. (2019, March).
In 2019 2nd International Conference on Communication, Computing and Digital systems (C-CODE) (pp. 143-148). IEEE.

2018

Conference ProceedingsMedical ImagingMachine Learning & Deep Learning
Deep Learning Based Automated Extraction of Intra-Retinal Layers for Analyzing Retinal Abnormalities
Taimur Hassan, M. Usman Akram, Anam Tariq, Furqan Masood, Ubaid ullah Yasin,
accepted in 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), 17-20 Sept 2018, Czech Republic

2017

ISI Indexed / Impact Factor Journal PapersIF 2.01Embedded SystemsMachine Learning & Deep Learning
Multiprocessor architecture for real-time applications using mean shift clustering.
Tehreem, Amna, Sajid Gul Khawaja, Asad Mansoor Khan, Muhammad Usman Akram, and Shoab A. Khan.
Journal of Real-Time Image Processing (2017): 1-14.
Non Impact Factor Indexed JournalsMedical ImagingMachine Learning & Deep Learning
A Comparison of Mean Models and Clustering Techniques for Vertebra Detection and Region Separation from C-Spine X-Rays
Mehmood, M.Usman Akram, A. Tariq, A. Fatima,
Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1758-1770 (2017).

2016

ISI Indexed / Impact Factor Journal PapersIF 0.471Embedded SystemsMachine Learning & Deep Learning
Network-on-Chip based MPSoC architecture for k-mean clustering algorithm.
Khawaja, Sajid Gul, Usman Akram, Shoab Ahmed Khan, Arslan Shaukat, and Saad Rehman.
Microprocessors and Microsystems 46 (2016): 1-10.
Non Impact Factor Indexed JournalsMedical ImagingMachine Learning & Deep LearningInternet of Things
Vertebra Localization Using Shape Based Analysis and Unsupervised Clustering from X-ray Images
Anum Mehmood, M. Usman Akram, Mahmood Akhtar,
PJCIS (2016), Vol. 1, No. 1 : 29-41
Conference ProceedingsMachine Learning & Deep Learning
Implementation and evaluation of optimized algorithm for software architectures analysis through unsupervised learning (clustering).
Khan, Qadeem, Usman Akram, Wasi Haider Butt, and Saad Rehman.
In Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2016 17th International Conference on, pp. 266-276. IEEE, 2016.
Conference ProceedingsEmbedded SystemsMachine Learning & Deep Learning
A novel multiprocessor architecture for k-means clustering algorithm based on network-on-chip.
Khawaja, Sajid Gul, Muhammad Usman Akram, Shoab A. Khan, and Ammar Ajmal.
In Multi-Topic Conference (INMIC), 2016 19th International, pp. 1-5. IEEE, 2016.
Conference ProceedingsEmbedded SystemsMachine Learning & Deep Learning
A Novel Architecture for k-means Clustering Algorithm.
Khawaja, S. G., Asad Mansoor Khan, Usman Akram, and Shoab A. Khan.
In International Afro-European Conference for Industrial Advancement, pp. 311-320. Springer, Cham, 2016.
Conference ProceedingsMachine Learning & Deep Learning
Unsupervised Neural Network optimized with Sequential Quadratic Programming for Linear and Non-Linear Dynamical Systems.
Basit, M., Arslan Shaukat, Usman Akram, and Umair Zafar Khan.
In Proceedings of the 8th International Conference on Signal Processing Systems, pp. 183-188. ACM, 2016.
Conference ProceedingsMedical ImagingMachine Learning & Deep Learning
Differentiation of blood vessels in retina into arteries and veins using neural network.
Ayub, Lubna, Abdul samad Khan, Javeria Ayub, Sara Ayub, Usman Akram, Samra Irshad, and Imran Basit.
In Computing, Electronic and Electrical Engineering (ICE Cube), 2016 International Conference on, pp. 301-306. IEEE, 2016.
Conference ProceedingsMedical ImagingMachine Learning & Deep Learning
Glaucoma detection through optic disc and cup segmentation using K-mean clustering.
Ayub, Javeria, Jamil Ahmad, Jan Muhammad, Lubna Aziz, Sara Ayub, Usman Akram, and Imran Basit.
In Computing, Electronic and Electrical Engineering (ICE Cube), 2016 International Conference on, pp. 143-147. IEEE, 2016.

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Publications

2020

Analysis of optical coherence tomography images using deep convolutional neural network for maculopathy grading.

Multistage Deep Neural Network Framework for People Detection and Localization Using Fusion of Visible and Thermal Images.

Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression.

Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis.

CNN and LSTM-Based Emotion Charting Using Physiological Signals

RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology.

Exploiting the Transferability of Deep Learning Systems Across Multi-modal Retinal Scans for Extracting Retinopathy Lesions.

2019

A Machine Learning Technique to Classify LSST Observed Astronomical Objects Based on Photometric Data

Person detection by fusion of visible and thermal images using convolutional neural network

2018

Deep Learning Based Automated Extraction of Intra-Retinal Layers for Analyzing Retinal Abnormalities

2017

Multiprocessor architecture for real-time applications using mean shift clustering.

A Comparison of Mean Models and Clustering Techniques for Vertebra Detection and Region Separation from C-Spine X-Rays

2016

Network-on-Chip based MPSoC architecture for k-mean clustering algorithm.

Vertebra Localization Using Shape Based Analysis and Unsupervised Clustering from X-ray Images

Implementation and evaluation of optimized algorithm for software architectures analysis through unsupervised learning (clustering).

A novel multiprocessor architecture for k-means clustering algorithm based on network-on-chip.

A Novel Architecture for k-means Clustering Algorithm.

Unsupervised Neural Network optimized with Sequential Quadratic Programming for Linear and Non-Linear Dynamical Systems.

Differentiation of blood vessels in retina into arteries and veins using neural network.

Glaucoma detection through optic disc and cup segmentation using K-mean clustering.

2020

Analysis of optical coherence tomography images using deep convolutional neural network for maculopathy grading.

Multistage Deep Neural Network Framework for People Detection and Localization Using Fusion of Visible and Thermal Images.

Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression.

Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis.

CNN and LSTM-Based Emotion Charting Using Physiological Signals

RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology.

Exploiting the Transferability of Deep Learning Systems Across Multi-modal Retinal Scans for Extracting Retinopathy Lesions.

2019

A Machine Learning Technique to Classify LSST Observed Astronomical Objects Based on Photometric Data

Person detection by fusion of visible and thermal images using convolutional neural network

2018

Deep Learning Based Automated Extraction of Intra-Retinal Layers for Analyzing Retinal Abnormalities

2017

Multiprocessor architecture for real-time applications using mean shift clustering.

A Comparison of Mean Models and Clustering Techniques for Vertebra Detection and Region Separation from C-Spine X-Rays

2016

Network-on-Chip based MPSoC architecture for k-mean clustering algorithm.

Vertebra Localization Using Shape Based Analysis and Unsupervised Clustering from X-ray Images

Implementation and evaluation of optimized algorithm for software architectures analysis through unsupervised learning (clustering).

A novel multiprocessor architecture for k-means clustering algorithm based on network-on-chip.

A Novel Architecture for k-means Clustering Algorithm.

Unsupervised Neural Network optimized with Sequential Quadratic Programming for Linear and Non-Linear Dynamical Systems.

Differentiation of blood vessels in retina into arteries and veins using neural network.

Glaucoma detection through optic disc and cup segmentation using K-mean clustering.