2.6k citations · 2.8k across the 24 of their papers we have counts for
24 papers
CB-HVTNet: A channel-boosted hybrid vision transformer network for lymphocyte assessment in histopathological images
Momina Liaqat Ali, Zunaira Rauf, Asifullah Khan +3
Transformers, due to their ability to learn long range dependencies, have overcome the shortcomings of convolutional neural networks (CNNs) for global perspective learning. Therefo…
MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation
Abdul Rehman Khan, Asifullah Khan
Since their emergence, Convolutional Neural Networks (CNNs) have made significant strides in medical image analysis. However, the local nature of the convolution operator may pose…
Early Risk Prediction of Chronic Myeloid Leukemia with Protein Sequences using Machine Learning-based Meta-Ensemble
Madiha Hameed, Muhammad Bilal, Tuba Majid +2
Leukemia, the cancer of blood cells, originates in the blood-forming cells of the bone marrow. In Chronic Myeloid Leukemia (CML) conditions, the cells partially become mature that…
Deep Neural Networks based Meta-Learning for Network Intrusion Detection
Anabia Sohail, Bibi Ayisha, Irfan Hameed +3
The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection s…
Traffic Management of Autonomous Vehicles using Policy Based Deep Reinforcement Learning and Intelligent Routing
Anum Mushtaq, Irfan ul Haq, Muhammad Azeem Sarwar +2
Deep Reinforcement Learning (DRL) uses diverse, unstructured data and makes RL capable of learning complex policies in high dimensional environments. Intelligent Transportation Sys…
A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
Asifullah Khan, Saddam Hussain Khan, Mahrukh Saif +3
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 devastat…
Autonomous Drone Swarm Navigation and Multi-target Tracking in 3D Environments with Dynamic Obstacles
Suleman Qamar, Saddam Hussain Khan, Muhammad Arif Arshad +2
Autonomous modeling of artificial swarms is necessary because manual creation is a time intensive and complicated procedure which makes it impractical. An autonomous approach emplo…
A New Deep Hybrid Boosted and Ensemble Learning-based Brain Tumor Analysis using MRI
Mirza Mumtaz Zahoor, Shahzad Ahmad Qureshi, Saddam Hussain Khan +1
Brain tumors analysis is important in timely diagnosis and effective treatment to cure patients. Tumor analysis is challenging because of tumor morphology like size, location, text…
IoT Malware Detection Architecture using a Novel Channel Boosted and Squeezed CNN
Muhammad Asam, Saddam Hussain Khan, Tauseef Jamal +1
Interaction between devices, people, and the Internet has given birth to a new digital communication model, the Internet of Things (IoT). The seamless network of these smart device…
Segmentation of Shoulder Muscle MRI Using a New Region and Edge based Deep Auto-Encoder
Saddam Hussain Khan, Asifullah Khan, Yeon Soo Lee +2
Automatic segmentation of shoulder muscle MRI is challenging due to the high variation in muscle size, shape, texture, and spatial position of tears. Manual segmentation of tear an…
Malware Classification Using Deep Boosted Learning
Muhammad Asam, Saddam Hussain Khan, Tauseef Jamal +2
Malicious activities in cyberspace have gone further than simply hacking machines and spreading viruses. It has become a challenge for a nations survival and hence has evolved to c…
COVID-19 Detection in Chest X-Ray Images using a New Channel Boosted CNN
Saddam Hussain Khan, Anabia Sohail, Asifullah Khan
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 det…
Extracting Signals of Higgs Boson From Background Noise Using Deep Neural Networks
Muhammad Abbas, Asifullah Khan, Aqsa Saeed Qureshi +1
Higgs boson is a fundamental particle, and the classification of Higgs signals is a well-known problem in high energy physics. The identification of the Higgs signal is a challengi…
Classification and Region Analysis of COVID-19 Infection using Lung CT Images and Deep Convolutional Neural Networks
Saddam Hussain Khan, Anabia Sohail, Asifullah Khan +1
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 treatme…
Wind Speed Prediction using Deep Ensemble Learning with a Jet-like Architecture
Aqsa Saeed Qureshi, Asifullah Khan, Muhammad Waleed Khan
The wind is one of the most increasingly used renewable energy resources. Accurate and reliable forecast of wind speed is necessary for efficient power production; however, it is n…
Deep Object Detection based Mitosis Analysis in Breast Cancer Histopathological Images
Anabia Sohail, Muhammad Ahsan Mukhtar, Asifullah Khan +3
Empirical evaluation of breast tissue biopsies for mitotic nuclei detection is considered an important prognostic biomarker in tumor grading and cancer progression. However, automa…
Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection Technique
Muhammad Furqan Rafique, Muhammad Ali, Aqsa Saeed Qureshi +2
In the case of malware analysis, categorization of malicious files is an essential part after malware detection. Numerous static and dynamic techniques have been reported so far fo…
Ransomware Analysis using Feature Engineering and Deep Neural Networks
Arslan Ashraf, Abdul Aziz, Umme Zahoora +2
Detection and analysis of a potential malware specifically, used for ransom is a challenging task. Recently, intruders are utilizing advanced cryptographic techniques to get hold o…
A Recent Survey on the Applications of Genetic Programming in Image Processing
Asifullah Khan, Aqsa Saeed Qureshi, Noorul Wahab +2
Genetic Programming (GP) has been primarily used to tackle optimization, classification, and feature selection related tasks. The widespread use of GP is due to its flexible and co…
Transfer Learning and Meta Classification Based Deep Churn Prediction System for Telecom Industry
Uzair Ahmed, Asifullah Khan, Saddam Hussain Khan +3
A churn prediction system guides telecom service providers to reduce revenue loss. However, the development of a churn prediction system for a telecom industry is a challenging tas…
A Survey of the Recent Architectures of Deep Convolutional Neural Networks
Asifullah Khan, Anabia Sohail, Umme Zahoora +1
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 Pro…
Adaptive Transfer Learning in Deep Neural Networks: Wind Power Prediction using Knowledge Transfer from Region to Region and Between Different Task Domains
Aqsa Saeed Qureshi, Asifullah Khan
Transfer Learning (TL) in Deep Neural Networks is gaining importance because in most of the applications, the labeling of data is costly and time-consuming. Additionally, TL also p…
Deep Belief Networks Based Feature Generation and Regression for Predicting Wind Power
Asifullah Khan, Aneela Zameer, Tauseef Jamal +1
Wind energy forecasting helps to manage power production, and hence, reduces energy cost. Deep Neural Networks (DNN) mimics hierarchical learning in the human brain and thus posses…
A New Channel Boosted Convolutional Neural Network using Transfer Learning
Asifullah Khan, Anabia Sohail, Amna Ali
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…