Ganesan, Swathi ORCID: https://orcid.org/0000-0002-6278-2090, Somasiri, Nalinda ORCID: https://orcid.org/0000-0001-6311-2251 and Colombage, Chandima (2023) Deep Learning Approaches for Accurate Sentiment Analysis of Online Consumer Feedback. In: 2023 International Conference on Computer Communication and Informatics (ICCCI), 23 January 2023.

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Abstract

Over the earlier time, a category of machine learning, called deep learning, has attained significant achievements in several computer vision tasks such as image classification, object detection, semantic segmentation, pattern recognition and image classification generation. Deep learning objectives at finding various levels of dispersed representations, which have been proven to be discriminatively effective in many tasks. Distributed statement depicts similar information highlights across different adaptable and reliant layers. Each layer characterizes the data with a similar degree of exactness, however adapted to the degree of scale. The implementation of deep learning techniques depends greatly on the variety of data interpretation (or features) on which they are used. Artificial intelligence plans to understand interpretations of information regularly by changing over it or isolating components as of it, which creates it simpler to play out an undertaking like order or extrapolation.

Item Type:	Conference or Workshop Item (Paper)
Status:	Published
Subjects:	T Technology > T Technology (General)
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/7366

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