Results 21 to 30 of about 12,040,618 (293)
Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction [PDF]
, 2004 The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an ...
Ebrahimi Touradj +5 more
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Image semantic segmentation method based on GAN network and ENet model
The Journal of Engineering, 2021 Currently, image semantic segmentation has problems such as low accuracy and long running time. This paper proposes an image semantic segmentation method based on generative adversarial network and ENet model combined with deep neural network.
Huiyi Li
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Real-time Semantic Segmentation Method Based on Multi-path Feature Extraction [PDF]
Jisuanji kexue, 2022 The application of deep learning in the field of image semantic segmentation has greatly improved the accuracy of segmentation,but due to the limitations of speed and memory,these models can not be directly applied to embedded devices for real-time ...
CHENG Cheng, JIANG Ai-lian
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WAILS: Watershed Algorithm With Image-Level Supervision for Weakly Supervised Semantic Segmentation
IEEE Access, 2019 Image semantic segmentation has great development in many fields, and the lack of fully supervised segmentation labels has always been a major problem in the development of image semantic segmentation.
Hongming Zhou +4 more
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ATLANTIS: A benchmark for semantic segmentation of waterbody images [PDF]
Environmental Modelling & Software, 2022 Vision-based semantic segmentation of waterbodies and nearby related objects provides important information for managing water resources and handling flooding emergency. However, the lack of large-scale labeled training and testing datasets for water-related categories prevents researchers from studying water-related issues in the computer vision field.
Seyed Mohammad Hassan Erfani +4 more
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Graph-FCN for Image Semantic Segmentation [PDF]
, 2019 Semantic segmentation with deep learning has achieved great progress in classifying the pixels in the image. However, the local location information is usually ignored in the high-level feature extraction by the deep learning, which is important for image semantic segmentation.
Yi Lu +3 more
openaire +2 more sources
Automatic texture segmentation for content-based image retrieval application [PDF]
, 2006 In this article, a brief review on texture segmentation is presented, before a novel automatic texture segmentation algorithm is developed. The algorithm is based on a modified discrete wavelet frames and the mean shift algorithm.
Fauzi, M.F.A. +3 more
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Semantic Segmentation of Seismic Images
CoRR, 2019 Almost all work to understand Earth's subsurface on a large scale relies on the interpretation of seismic surveys by experts who segment the survey (usually a cube) into layers; a process that is very time demanding. In this paper, we present a new deep neural network architecture specially designed to semantically segment seismic images with a minimal
Daniel Civitarese +3 more
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Scene-Aware Deep Networks for Semantic Segmentation of Images
IEEE Access, 2019 Scene classification and semantic segmentation are two important research directions in computer vision. They are widely used in the research of automatic driving and human–computer interaction.
Zhike Yi +5 more
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Image semantic segmentation method based on GAN network and ERFNet model
The Journal of Engineering, 2021 This article addresses the problems of traditional methods in image semantic segmentation, such as insufficient segmentation of small‐scale targets and weak anti‐noise ability.
Chaoxian Dong
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