Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Sohail, Anabia"'
Autor:
Ali, Momina Liaqat, Rauf, Zunaira, Khan, Asifullah, Sohail, Anabia, Ullah, Rafi, Gwak, Jeonghwan
Transformers, due to their ability to learn long range dependencies, have overcome the shortcomings of convolutional neural networks (CNNs) for global perspective learning. Therefore, they have gained the focus of researchers for several vision relat
Externí odkaz:
http://arxiv.org/abs/2305.09211
Autor:
Khan, Asifullah, Rauf, Zunaira, Sohail, Anabia, Rehman, Abdul, Asif, Hifsa, Asif, Aqsa, Farooq, Umair
Publikováno v:
Artificial Intelligence Review (2023): 1-54
Vision transformers have become popular as a possible substitute to convolutional neural networks (CNNs) for a variety of computer vision applications. These transformers, with their ability to focus on global relationships in images, offer large lea
Externí odkaz:
http://arxiv.org/abs/2305.09880
Autor:
Sohail, Anabia, Ayisha, Bibi, Hameed, Irfan, Zafar, Muhammad Mohsin, Alquhayz, Hani, Khan, Asifullah
The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as n
Externí odkaz:
http://arxiv.org/abs/2302.09394
Autor:
Khan, Asifullah, Khan, Saddam Hussain, Saif, Mahrukh, Batool, Asiya, Sohail, Anabia, Khan, Muhammad Waleed
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. Deep learning (DL) techniques have proved help
Externí odkaz:
http://arxiv.org/abs/2202.06372
COVID-19 is a highly contagious respiratory infection that has affected a large population across the world and continues with its devastating consequences. It is imperative to detect COVID-19 at the earliest to limit the span of infection. In this w
Externí odkaz:
http://arxiv.org/abs/2012.05073
COVID-19 is a global health problem. Consequently, early detection and analysis of the infection patterns are crucial for controlling infection spread as well as devising a treatment plan. This work proposes a two-stage deep Convolutional Neural Netw
Externí odkaz:
http://arxiv.org/abs/2009.08864
Autor:
Sohail, Anabia, Mukhtar, Muhammad Ahsan, Khan, Asifullah, Zafar, Muhammad Mohsin, Zameer, Aneela, Khan, Saranjam
Empirical evaluation of breast tissue biopsies for mitotic nuclei detection is considered an important prognostic biomarker in tumor grading and cancer progression. However, automated mitotic nuclei detection poses several challenges because of the u
Externí odkaz:
http://arxiv.org/abs/2003.08803
Deep Convolutional Neural Network (CNN) is a special type of Neural Networks, which has shown exemplary performance on several competitions related to Computer Vision and Image Processing. Some of the exciting application areas of CNN include Image C
Externí odkaz:
http://arxiv.org/abs/1901.06032
We present a novel architectural enhancement of Channel Boosting in a deep convolutional neural network (CNN). This idea of Channel Boosting exploits both the channel dimension of CNN (learning from multiple input channels) and Transfer learning (TL)
Externí odkaz:
http://arxiv.org/abs/1804.08528
Autor:
Zafar, Muhammad Mohsin, Rauf, Zunaira, Sohail, Anabia, Khan, Abdul Rehman, Obaidullah, Muhammad, Khan, Saddam Hussain, Lee, Yeon Soo, Khan, Asifullah
Publikováno v:
In Photodiagnosis and Photodynamic Therapy March 2022 37