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13th International Conference on Computer and Knowledge Engineering
A Deep CNN Model Based Ensemble Approach for Semantic and Instance Segmentation of Indoor Environment
Authors :
Sajad Rezaei
1
Jafar Tanha
2
Zahra Jafari
3
SeyedEhsan Roshan
4
Mohammad-Amin Memar Kochebagh
5
1- Department of electrical and computer engineering University of Tabriz Tabriz, Iran
2- Department of electrical and computer engineering University of Tabriz Tabriz, Iran
3- Department of electrical and computer engineering University of Tabriz Tabriz, Iran
4- Department of electrical and computer engineering University of Tabriz Tabriz, Iran
5- Department of electrical and computer engineering University of Tabriz Tabriz, Iran
Keywords :
Semantic Segmentation،Instance Segmentation،Convolutional Neural Networks،Ensemble Models
Abstract :
Image segmentation has emerged as a popular and challenging task in computer vision. Deep learning methods have demonstrated significant success in this domain. In this paper, we propose a deep ensemble model for semantic segmentation of indoor scenes. Our ensemble model combines three distinct deep learning models to enhance both diversity and accuracy. Additionally, we customize YOLOv8 for instance-level segmentation of indoor environments. A comprehensive set of experiments on the publicly available data set demonstrates that our model achieves the highest IoU compared to state-of-the-art deep learning models.
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