International Conference on Computer and Knowledge Engineering

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A Deep CNN Model Based Ensemble Approach for Semantic and Instance Segmentation of Indoor Environment

Authors :

Sajad Rezaei¹ Jafar Tanha² Zahra Jafari³ SeyedEhsan Roshan⁴ Mohammad-Amin Memar Kochebagh⁵

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.