Search Results for author: Saddam Hussain Khan

Found 15 papers, 3 papers with code

COVID-19 Infection Analysis Framework using Novel Boosted CNNs and Radiological Images

no code implementations6 Feb 2023 Saddam Hussain Khan

Moreover, the various boosted channels are obtained by introducing the new CB and Transfer Learning (TL) concept in STM blocks to capture small illumination and texture variations of COVID-19-specific images.

Transfer Learning

A New Deep Boosted CNN and Ensemble Learning based IoT Malware Detection

no code implementations15 Dec 2022 Saddam Hussain Khan, Wasi Ullah

In this regard, we have developed a new malware detection framework, Deep Squeezed-Boosted and Ensemble Learning (DSBEL), comprised of novel Squeezed-Boosted Boundary-Region Split-Transform-Merge (SB-BR-STM) CNN and ensemble learning.

Ensemble Learning Malware Analysis +2

Malaria Parasitic Detection using a New Deep Boosted and Ensemble Learning Framework

no code implementations5 Dec 2022 Saddam Hussain Khan

The proposed DBEL framework implicates the stacking of prominent and diverse boosted channels and provides the generated discriminative features of the developed Boosted-BR-STM to the ensemble of ML classifiers.

Ensemble Learning Transfer Learning

Brain Tumor MRI Classification using a Novel Deep Residual and Regional CNN

no code implementations29 Nov 2022 Mirza Mumtaz Zahoor, Saddam Hussain Khan

Brain tumor classification is crucial for clinical analysis and an effective treatment plan to cure patients.

COVID-19 Detection and Analysis From Lung CT Images using Novel Channel Boosted CNNs

no code implementations22 Sep 2022 Saddam Hussain Khan

In the first phase, a novel SB-STM-BRNet CNN is developed, incorporating a new channel Squeezed and Boosted (SB) and dilated convolutional-based Split-Transform-Merge (STM) block to detect COVID-19 infected lung CT images.

COVID-19 Diagnosis Transfer Learning

A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron

no code implementations13 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.

COVID-19 Diagnosis

IoT Malware Detection Architecture using a Novel Channel Boosted and Squeezed CNN

no code implementations8 Feb 2022 Muhammad Asam, Saddam Hussain Khan, Tauseef Jamal, Asifullah Khan

The proposed architecture exploits the concepts of edge and smoothing, multi-path dilated convolutional operations, channel squeezing, and boosting in CNN.

Malware Detection

A New Deep Hybrid Boosted and Ensemble Learning-based Brain Tumor Analysis using MRI

no code implementations14 Jan 2022 Mirza Mumtaz Zahoor, Shahzad Ahmad Qureshi, Saddam Hussain Khan, Asifullah Khan

While in the second phase, a new hybrid features fusion-based brain tumor classification approach is proposed, comprised of dynamic-static feature and ML classifier to categorize different tumor types.

Ensemble Learning

Segmentation of Shoulder Muscle MRI Using a New Region and Edge based Deep Auto-Encoder

no code implementations26 Aug 2021 Saddam Hussain Khan, Asifullah Khan, Yeon Soo Lee, Mehdi Hassan, Woong Kyo jeong

The performances of the proposed MRI segmentation based DAE architectures have been tested using a 3D MRI shoulder muscle dataset using the hold-out cross-validation technique.

MRI segmentation Transfer Learning

Malware Classification Using Deep Boosted Learning

no code implementations8 Jul 2021 Muhammad Asam, Saddam Hussain Khan, Tauseef Jamal, Umme Zahoora, Asifullah Khan

In the hybrid learning, Deep features are extracted from customized CNN architectures and fed into the conventional machine learning classifier to improve the classification performance.

Classification Malware Classification +1

COVID-19 Detection in Chest X-Ray Images using a New Channel Boosted CNN

2 code implementations8 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.

Domain Adaptation Transfer Learning

Classification and Region Analysis of COVID-19 Infection using Lung CT Images and Deep Convolutional Neural Networks

1 code implementation16 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.

Semantic Segmentation

Transfer Learning and Meta Classification Based Deep Churn Prediction System for Telecom Industry

no code implementations18 Jan 2019 Uzair Ahmed, Asifullah Khan, Saddam Hussain Khan, Abdul Basit, Irfan Ul Haq, Yeon Soo Lee

However, the development of a churn prediction system for a telecom industry is a challenging task, mainly due to the large size of the data, high dimensional features, and imbalanced distribution of the data.

General Classification Transfer Learning

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