Browsing by Author "Bhat, H."

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    A hybrid approach for nucleus stain separation in histopathological images
    (Institute of Electrical and Electronics Engineers Inc., 2017) Bhat, H.; Kanakatte, A.; Nayak, R.; Gubbi, J.
    Difficulties in automation of histology image analysis are caused due to varying stain colors in the histology slides and the interaction of stains. Incorrect stain separation results in incorrect nucleus segmentation. A new hybrid algorithm has been proposed combining de-staining and wedge separation algorithms, which provides better stain separation and maintains color integrity of the input image. The proposed algorithm is tested on 36 histopathological images covering varying tissues and compared with popular methods in the area with excellent results in high nuclei density category. © 2017 IEEE.
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    An Artificial Intelligent Enabled Framework for Malware Detection
    (CRC Press, 2023) Singh, M.P.; Bhat, H.; Kartikeya, S.; Choudhary, S.
    Malware (Malicious Software) has become a severe threat to society, growing in numbers and sophistication daily. Malware writers increasingly use advanced techniques like server-side polymorphism, code obfuscation, and encryption to evade the detection by traditional signature-based malware detection approaches. Several Machine Learning (ML) and Artificial Intelligence (AI) driven approaches have been proposed in the last few years to replace conventional signature-based methods. This chapter presents an intelligent malware detection framework based on static analysis of Windows API calls and PE header files. It uses an ensemble approach and the Chi-square-based feature selection method. The framework also uses locality-sensitive hashing (LSH) to store all previously seen malware and detect known variants to increase computational efficiency. Experimental results demonstrate the effectiveness of the proposed framework. © 2024 selection and editorial matter, Mayank Swarnkar and Shyam Singh Rajput; individual chapters, the contributors.
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    Dynamic resource allocation for multi-tier applications in cloud
    (2016) Achar, R.; Santhi Thilagam, P.; Meghana; Niha, Fathima, Haris, B.; Bhat, H.; Ekta, K.
    Increasing demand for computing resources and widespread adaption of service-oriented architecture has made cloud as a new IT delivery mechanism. Number of cloud providers offer computing resources in the form of virtual machines to the cloud customers based on business requirements. Load experienced by the present business applications hosted in cloud are dynamic in nature. This creates a need for a mechanism which allocates resources dynamically to the applications in order to minimize performance degradations. This paper presents a mechanism which dynamically allocates the resources based on load of the application using vertical and horizontal scaling. Cloud environment is set up using Xen cloud platform and multi-tier web application is deployed on virtual machines. Experimental study conducted for various loads show that proposed mechanism ensures the response time is within the acceptable range. � Springer Science+Business Media Singapore 2016.
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    Dynamic resource allocation for multi-tier applications in cloud
    (Springer Verlag service@springer.de, 2016) Achar, R.; Santhi Thilagam, P.; Meghana; Niha Fathima Haris, B.; Bhat, H.; Ekta, K.
    Increasing demand for computing resources and widespread adaption of service-oriented architecture has made cloud as a new IT delivery mechanism. Number of cloud providers offer computing resources in the form of virtual machines to the cloud customers based on business requirements. Load experienced by the present business applications hosted in cloud are dynamic in nature. This creates a need for a mechanism which allocates resources dynamically to the applications in order to minimize performance degradations. This paper presents a mechanism which dynamically allocates the resources based on load of the application using vertical and horizontal scaling. Cloud environment is set up using Xen cloud platform and multi-tier web application is deployed on virtual machines. Experimental study conducted for various loads show that proposed mechanism ensures the response time is within the acceptable range. © Springer Science+Business Media Singapore 2016.
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    A hybrid approach for nucleus stain separation in histopathological images
    (2017) Bhat, H.; Kanakatte, A.; Nayak, R.; Gubbi, J.
    Difficulties in automation of histology image analysis are caused due to varying stain colors in the histology slides and the interaction of stains. Incorrect stain separation results in incorrect nucleus segmentation. A new hybrid algorithm has been proposed combining de-staining and wedge separation algorithms, which provides better stain separation and maintains color integrity of the input image. The proposed algorithm is tested on 36 histopathological images covering varying tissues and compared with popular methods in the area with excellent results in high nuclei density category. � 2017 IEEE.