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An Abstraction of Semantic Segmentation Algorithms
2020 International Conference on Machine Vision and Image Processing (MVIP), 2020semantic segmentation is a process of classifying each pixel in the image. Due to its advantages, semantic segmentation is used in many tasks like cancer detection, robot-assisted surgery, satellite images, self-driving car, etc. in this process, accuracy and efficiency are the two crucial goals for this purpose, there are several state-of-the-art ...
Reihaneh Teymoori +3 more
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Benchmarking algorithms for food localization and semantic segmentation
International Journal of Machine Learning and Cybernetics, 2020The problem of food segmentation is quite challenging since food is characterized by intrinsic high intra-class variability. Also, segmentation of food images taken in-the-wild may be characterized by acquisition artifacts, and that could be problematic for the segmentation algorithms.
Sinem Aslan +3 more
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Scene Classification Algorithm Based on Semantic Segmented Objects
2021 IEEE International Conference on Consumer Electronics (ICCE), 2021Scene classification is one of the important problems in image and video search and recommendation systems. We propose an efficient scene classification method for three different classes by detecting objects in the scene. For detecting objects in an image, pre-trained semantic segmentation model is used.
Woon-Ha Yeo +4 more
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A semantics based segmentation algorithm for scene images
2011 IEEE International Conference on Cloud Computing and Intelligence Systems, 2011This paper proposes and evaluates a new semantics based segmentation algorithm for scene images. This algorithm has two phases: the initial segmentation based on color-spatial information and region merging based semantics information. The initial segmentation uses an automatic region growth method without the need of seeds.
Xiaoru Wang, Junping Du 0001, Jie Liu
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Semantic image segmentation using the ICM algorithm
2017 IEEE International Conference on Image Processing (ICIP), 2017Semantic image segmentation has recently become the focus of considerable interest. This task consists in assigning a predefined class label to each pixel (or pre-segmented region) in an image. To address the complexity challenge of this task, we develop, in this work, a novel and simple energy-minimization model.
Lazhar Khelifi, Max Mignotte
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Semantic relevance of current image segmentation algorithms
2009 10th Workshop on Image Analysis for Multimedia Interactive Services, 2009Several image classification problems are handled using a classical statistical pattern recognition methodology: image segmentation, visual feature extraction, classification. The accuracy of the solution is typically measured by comparing automatic results with manual classification ones, where the distinction between these three steps is not clear at
Farhan Riaz +2 more
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Semantic Segmentation Algorithm of Night Images Based on Attention Mechanism
Journal of Circuits, Systems and Computers, 2023At present, there are many semantic segmentation algorithms with excellent performance for intelligent driving vehicles, but most of them only work well on scenes with good illumination. In order to solve the problem of scene segmentation under low illumination, this paper proposes a novel semantic segmentation algorithm that combines visible and ...
Xiaona Xie +5 more
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A General Lane Detection Algorithm Based on Semantic Segmentation
Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, 2018With the development of artificial intelligent (AI), more and more fields are embracing the AI technology. Intelligent driving is one of the these fields. The environment perception is the fundamental of intelligent driving while lane detection is one of important part of environment perception.
Renrong Shao, Baojian Qian, Jun Guo
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Image Semantics Segmentation using Watershed Algorithm
2006 IEEE International Conference on Service Operations and Logistics, and Informatics, 2006In this paper a novel image semantics segmentation algorithm is proposed, which combines edge and region-merged based techniques. First, an edge-preserving statistical noise reduction approach is used as a preprocessing stage in order to compute an accurate estimate of an image gradient.
Miao chengliang, Xie shengli, Yu weiyu
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Semantic image segmentation algorithm in a deep learning computer network
Multimedia Systems, 2020Semantic image segmentation in computer networks is designed to determine the category to which each pixel in an image belongs. It is a basic computer vision task and has a very wide range of applications in practice. In recent years, semantic image segmentation algorithms in computer networks based on deep learning have attracted widespread attention ...
Defu He, Chao Xie
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