Accuracy Enhancement of Portrait Segmentation by Ensembling Deep Learning Models
- Title
- Accuracy Enhancement of Portrait Segmentation by Ensembling Deep Learning Models
- Creator
- Kim Y.W.; Innila Rose J.; Krishna A.V.N.
- Description
- Portrait segmentation is widely used as a preprocessing step in multiple applications. The accuracy of portrait segmentation models indicates its reliability. In recent times, portrait segmentation using deep learning models have achieved significant success in performance and accuracy. However, these portrait segmentation models are limited to a single model. In this paper, we propose ensemble approach using multiple portrait segmentation models to improve the segmentation accuracy. The result of experiment shows that the proposed ensemble approach produces better accuracy than individual models. Accuracy of single models and proposed ensemble approach were compared with Intersection over Union (IoU) metric and false prediction rate to evaluate the accuracy performance. The result shows reduced false negative rate and false discovery rate, this reduction in false prediction has enabled ensemble approach to produce segmented images with optimized error and improved result of segmentation in portrait area of human body than individual portrait segmentation models 2020 IEEE.
- Source
- Proceedings - 2020 5th International Conference on Research in Computational Intelligence and Communication Networks, ICRCICN 2020, pp. 59-64.
- Date
- 2020-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Deep Learning; Ensemble Method; Portrait Segmentation; Simple Soft Voting; Weighted Soft Voting
- Coverage
- Kim Y.W., CHRIST (Deemed to Be University), Centre for Digital Innovation, Bangalore, India; Innila Rose J., CHRIST (Deemed to Be University), Centre for Digital Innovation, Bangalore, India; Krishna A.V.N., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-172818818-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Kim Y.W.; Innila Rose J.; Krishna A.V.N., “Accuracy Enhancement of Portrait Segmentation by Ensembling Deep Learning Models,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20658.