His scientific interests lie mostly in Artificial intelligence, Digital watermarking, Watermark, Pattern recognition and Support vector machine. His study looks at the relationship between Artificial intelligence and fields such as Machine learning, as well as how they intersect with chemical problems. His Digital watermarking study incorporates themes from Algorithm, Wavelet and Authentication.
The concepts of his Watermark study are interwoven with issues in Cover, Information hiding, Theoretical computer science and Robustness. His work in the fields of Pattern recognition, such as Polynomial kernel, intersects with other areas such as Polynomial. Asifullah Khan interconnects Pseudo amino acid composition and Bioinformatics in the investigation of issues within Support vector machine.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Support vector machine and Digital watermarking. As part of the same scientific family, Asifullah Khan usually focuses on Artificial intelligence, concentrating on Machine learning and intersecting with Data mining. His Pattern recognition study combines topics in areas such as Feature and Cluster analysis.
His Support vector machine research is multidisciplinary, relying on both Artificial neural network, Discriminative model, Pseudo amino acid composition and Bioinformatics. The Digital watermarking study combines topics in areas such as Watermark, Cover, Algorithm, Genetic programming and Wavelet transform. His Feature extraction course of study focuses on Random forest and Principal component analysis.
Asifullah Khan spends much of his time researching Artificial intelligence, Pattern recognition, Convolutional neural network, Feature vector and Deep learning. As part of his studies on Artificial intelligence, Asifullah Khan frequently links adjacent subjects like Machine learning. His research integrates issues of Breast cancer, Mitosis and Feature in his study of Pattern recognition.
Asifullah Khan combines subjects such as Feature engineering, Thresholding, Boosting, Malware and Feature extraction with his study of Convolutional neural network. The study incorporates disciplines such as Ensemble learning and Computer vision in addition to Deep learning. He has researched Artificial neural network in several fields, including Anomaly detection, Network security, Residual, One-class classification and Genetic programming.
Asifullah Khan mainly investigates Artificial intelligence, Artificial neural network, Convolutional neural network, Transfer of learning and Genetic programming. His biological study spans a wide range of topics, including Machine learning and Pattern recognition. His Machine learning research incorporates elements of Contextual image classification, Object detection, Feature extraction and Video processing.
Asifullah Khan focuses mostly in the field of Artificial neural network, narrowing it down to topics relating to Feature vector and, in certain cases, One-class classification, Residual, Anomaly detection and Network security. His research in Transfer of learning focuses on subjects like Classifier, which are connected to Telecommunications and Centroid. His work deals with themes such as Multispectral image, Image processing, Algorithm, Feature selection and Relevance vector machine, which intersect with Genetic programming.
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A survey of the recent architectures of deep convolutional neural networks
Asifullah Khan;Anabia Sohail;Umme Zahoora;Aqsa Saeed Qureshi.
Artificial Intelligence Review (2020)
Recent Progress on Generative Adversarial Networks (GANs): A Survey
Zhaoqing Pan;Weijie Yu;Xiaokai Yi;Asifullah Khan.
IEEE Access (2019)
A recent survey of reversible watermarking techniques
Asifullah Khan;Ayesha Siddiqa;Summuyya Munib;Sana Ambreen Malik.
Information Sciences (2014)
Wind power prediction using deep neural network based meta regression and transfer learning
Aqsa Saeed Qureshi;Asifullah Khan;Aneela Zameer;Anila Usman.
Applied Soft Computing (2017)
Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks
Aneela Zameer;Junaid Arshad;Asifullah Khan;Muhammad Asif Zahoor Raja.
Energy Conversion and Management (2017)
Discriminating outer membrane proteins with Fuzzy K-nearest Neighbor algorithms based on the general form of Chou's PseAAC.
Maqsood Hayat;Asifullah Khan.
Protein and Peptide Letters (2012)
Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.
Maqsood Hayat;Asifullah Khan.
Journal of Theoretical Biology (2011)
Intelligent reversible watermarking in integer wavelet domain for medical images
Muhammad Arsalan;Sana Ambreen Malik;Asifullah Khan.
Journal of Systems and Software (2012)
Two-phase deep convolutional neural network for reducing class skewness in histopathological images based breast cancer detection
Noorul Wahab;Asifullah Khan;Yeon Soo Lee.
Computers in Biology and Medicine (2017)
Churn prediction in telecom using Random Forest and PSO based data balancing in combination with various feature selection strategies
Adnan Idris;Muhammad Rizwan;Asifullah Khan.
Computers & Electrical Engineering (2012)
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