Landmark Recognition Using Ensemble-Based Machine Learning Models

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Author(s): Kanishk Bansal (Lovely Professional University, India)and Amar Singh Rana (Lovely Professional University, India)
Copyright: 2021
Pages: 11
Source title: Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease
Source Author(s)/Editor(s): Manikant Roy (Lovely Professional University, India)and Lovi Raj Gupta (Lovely Professional University, India)
DOI: 10.4018/978-1-7998-7188-0.ch005

Keywords: Knowledge Management and Library Science / Machine Learning / Medical Information Science Reference / Medical Technologies

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Abstract

Recognizing landmarks in images with machine learning is an excellent topic for research today. Landmark recognition is an important field in computer vision. In this field, we train the machine learning models to identify and recognize the closed distinctly distinguishable objects in a digital image. In general, if we consider a digital image to be a set of coordinates of different pixels, a landmark is said to be enclosed in that closed polygon formed by the pixels that may be considered as a distinct and distinguishable thing in one or the other sense. Landmark recognition is an important subject area of image classification since it is considered as one of the first steps towards reaching complete computer vision. The extremely broad definition of a landmark makes it eligible to be considered as one of the leading problems in image classification tasks. Since the task is considered to be a very broad one, the solutions to the task hold no easy procedures. This chapter explores landmark recognition using ensemble-based machine learning models.

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