Attentively Conditioned Generative Adversarial Network for Semantic Segmentation

Attentively Conditioned Generative Adversarial Network for Semantic Segmentation

Generative Adversarial Network has proven to produce state-of-the-art results by framing a generative modeling task into a supervised learning problem. In this paper, we propose Attentively Conditioned Generative Adversarial Network (ACGAN) for semantic segmentation by designing a segmentor model th...

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Bibliographic Details
Main Authors: Ariyo Oluwasanmi, Muhammad Umar Aftab, Akeem Shokanbi, Jehoiada Jackson, Bulbula Kumeda, Zhiquang Qin
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Generative adversarial network
deep convolutional neural network
attention network
conditional gan
semantic segmentation
deep learning
Online Access:https://ieeexplore.ieee.org/document/8993709/

Internet

https://ieeexplore.ieee.org/document/8993709/

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