no code implementations • 17 May 2023 • Asifullah Khan, Zunaira Rauf, Anabia Sohail, Abdul Rehman, Hifsa Asif, Aqsa Asif, Umair Farooq
This survey presents a taxonomy of the recent vision transformer architectures and more specifically that of the hybrid vision transformers.
no code implementations • 16 May 2023 • Momina Liaqat Ali, Zunaira Rauf, Asifullah Khan, Anabia Sohail, Rafi Ullah, Jeonghwan Gwak
To address this issue, we propose a Channel Boosted Hybrid Vision Transformer (CB HVT) that uses transfer learning to generate boosted channels and employs both transformers and CNNs to analyse lymphocytes in histopathological images.
no code implementations • 18 Feb 2023 • Anabia Sohail, Bibi Ayisha, Irfan Hameed, Muhammad Mohsin Zafar, Hani Alquhayz, Asifullah Khan
First, a hybrid feature space is created by integrating decision and feature spaces.
no code implementations • 13 Feb 2022 • Asifullah Khan, Saddam Hussain Khan, Mahrukh Saif, Asiya Batool, Anabia Sohail, Muhammad Waleed Khan
The Coronavirus (COVID-19) outbreak in December 2019 has become an ongoing threat to humans worldwide, creating a health crisis that infected millions of lives, as well as devastating the global economy.
1 code implementation • Photodiagnosis and Photodynamic Therapy 2021 • Muhammad Mohsin Zafar, Zunaira Rauf, Anabia Sohail, Abdul Rehman Khan, Muhammad Obaidullah, Saddam Hussain Khan, Yeon Soo Lee, Asifullah Khan
Results: The empirical evaluation on samples from LYSTO dataset shows that the proposed LSTAM-Net can learn variations in the images and precisely remove the hard negative stain artifacts with an F-score of 0. 74.
2 code implementations • 8 Dec 2020 • Saddam Hussain Khan, Anabia Sohail, Asifullah Khan
In this work, a new classification technique CB-STM-RENet based on deep Convolutional Neural Network (CNN) and Channel Boosting is proposed for the screening of COVID-19 in chest X-Rays.
1 code implementation • 16 Sep 2020 • Saddam Hussain Khan, Anabia Sohail, Asifullah Khan, Yeon Soo Lee
In the second stage, the CT images classified as infectious images are provided to the segmentation models for the identification and analysis of COVID-19 infectious regions.
no code implementations • 17 Mar 2020 • Anabia Sohail, Muhammad Ahsan Mukhtar, Asifullah Khan, Muhammad Mohsin Zafar, Aneela Zameer, Saranjam Khan
These challenges undermine the precision of the automated detection model and thus make detection difficult in a single phase.
no code implementations • 17 Jan 2019 • Asifullah Khan, Anabia Sohail, Umme Zahoora, Aqsa Saeed Qureshi
The availability of a large amount of data and improvement in the hardware technology has accelerated the research in CNNs, and recently interesting deep CNN architectures have been reported.
no code implementations • 23 Apr 2018 • Asifullah Khan, Anabia Sohail, Amna Ali
In the proposed methodology, a deep CNN is boosted by various channels available through TL from already trained Deep Neural Networks, in addition to its original channel.