Search Results - Very deep fully convolutional encoder–decoder network

Very deep fully convolutional encoder–decoder network based on wavelet transform for art image fusion in cloud computing environment by Chen, Tong, Yang, Juan

“… Therefore, we propose a very deep fully convolutional encoder–decoder network based on wavelet transform for art image fusion in the cloud computing environment…”
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A deep convolutional encoder-decoder architecture for autonomous fault detection of PV plants using multi-copters by Moradi Sizkouhi, Amirmohammad, Aghaei, Mohammadreza, Esmailifar, Sayyed Majid

“…•Feature extraction and up-sampling to pixel level output through a developed encoder-decoder network…”
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Deep Residual Encoder-Decoder Networks for Desert Seismic Noise Suppression by Ma, Haitao, Yao, Haiyang, Li, Yue, Wang, Hongzhou

“… In this letter, aiming at the intense interference of seismic exploration noise in the desert of China, a desert seismic noise reduction system based on deep residual encoder-decoder network is proposed…”
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A new fully convolutional neural network for semantic segmentation of polarimetric SAR imagery in complex land cover ecosystem by Mohammadimanesh, Fariba, Salehi, Bahram, Mahdianpari, Masoud, Gill, Eric, Molinier, Matthieu

“…[Display omitted] Despite the application of state-of-the-art fully Convolutional Neural Networks (CNNs…”
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Single infrared image enhancement using a deep convolutional neural network by Kuang, Xiaodong, Sui, Xiubao, Liu, Yuan, Chen, Qian, Gu, Guohua

“… In this paper, we propose a deep learning method for single infrared image enhancement. A fully convolutional neural network (CNN…”
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Efficient segmentation and classification of the tumor using improved encoder-decoder architecture in brain MRI images by Ingle, Archana, Roja, Mani, Sankhe, Manoj, Patkar, Deepak

“… precision and accuracy is indeed a time-consuming and very challenging task. So newer digital methods like deep learning algorithms are used for tumor diagnosis which may lead to far better results…”
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A Novel Recurrent Encoder-Decoder Structure for Large-Scale Multi-View Stereo Reconstruction From an Open Aerial Dataset by Liu, Jin, Ji, Shunping

“… However, these efforts were focused on close-range objects and only a very few of the deep learning-based methods were specifically designed for large-scale 3D urban reconstruction due to the lack…”
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P-LINKNET: LINKNET WITH SPATIAL PYRAMID POOLING FOR HIGH-RESOLUTION SATELLITE IMAGERY by Ding, Y., Wu, M., Xu, Y., Duan, S.

“…Automatic extraction of buildings from high-resolution remote sensing imagery is very useful in many applications such as city management, mapping, urban planning and geographic information updating…”
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Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction by Tao Zeng, Bian Wu, Jiayu Zhou, Davidson, Ian, Shuiwang Ji

“… Here, we proposed a general encoder-decoder network architecture that aims to addressing time-varying dense prediction problems…”
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Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping by Persello, C., Tolpekin, V.A., Bergado, J.R., de By, R.A.

“… Very High Resolution (VHR) satellite images can capture such information. However, the automated delineation of fields in smallholder farms is a challenging task…”
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Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections by Xiao-Jiao, Mao, Shen, Chunhua, Yu-Bin, Yang

“…In this paper, we propose a very deep fully convolutional encoding-decoding framework for image restoration such as denoising and super-resolution…”
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Hrlinknet: Linknet with High-Resolution Representation for High-Resolution Satellite Imagery by Wu, Muyu, Shu, Zhen, Zhang, Jinming, Hu, Xiangyun

“…Automatic extraction of buildings from high-resolution remote sensing imagery is very useful in many applications such as city management, mapping, urban planning and geographic information updating…”
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Deep smoke segmentation by Yuan, Feiniu, Zhang, Lin, Xia, Xue, Wan, Boyang, Huang, Qinghua, Li, Xuelong

“…Inspired by the recent success of fully convolutional networks (FCN) in semantic segmentation, we propose a deep smoke segmentation network to infer high quality segmentation masks from blurry smoke images…”
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Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans by B.N., Anoop, Li, Karl, Honnorat, Nicolas, Rashid, Tanweer, Wang, Di, Li, Jinqi, Fadaee, Elyas, Charisis, Sokratis, Walker, Jamie M., Richardson, Timothy E., Wolk, David A., Fox, Peter T., Cavazos, José E., Seshadri, Sudha, Wisse, Laura E.M., Habes, Mohamad

“… In this study, we explore the use of fully automated methods relying on state-of-the-art Deep Learning approaches to produce these annotations…”
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Real-Time Hybrid Multi-Sensor Fusion Framework for Perception in Autonomous Vehicles by Shahian Jahromi, Babak, Tulabandhula, Theja, Cetin, Sabri

“… Some fusion architectures can perform very well in lab conditions using powerful computational resources…”
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Fine-Grained Building Change Detection From Very High-Spatial-Resolution Remote Sensing Images Based on Deep Multitask Learning by Sun, Ying, Zhang, Xinchang, Huang, Jianfeng, Wang, Haiying, Xin, Qinchuan

“… Recently, fully convolutional neural networks (FCNs) have been proven to be capable of feature extraction and semantic segmentation of VHR images, but its ability in change detection is untested and unknown…”
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Unsupervised Spectral-Spatial Feature Learning via Deep Residual Conv-Deconv Network for Hyperspectral Image Classification by Lichao Mou, Ghamisi, Pedram, Xiao Xiang Zhu

“… Specifically, our network is based on the so-called encoder-decoder paradigm, i.e., the input 3-D hyperspectral patch is first transformed into a typically lower dimensional space via a convolutional subnetwork (encoder…”
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Encoder-Decoder based CNN and Fully Connected CRFs for Remote Sensed Image Segmentation by Gurumurthy, Vikas Agaradahalli

“… In this work, a deep Convolutional Neural Network (CNN) based on symmetric encoder-decoder architecture with skip connections is employed for the 2D semantic segmentation…”
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A Novel Recurrent Encoder-Decoder Structure for Large-Scale Multi-view Stereo Reconstruction from An Open Aerial Dataset by Liu, Jin, Ji, Shunping

“… However, these efforts were focused on close-range objects and only a very few of the deep learning-based methods were specifically designed for large-scale 3D urban reconstruction due to the lack…”
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Versatile Convolutional Networks Applied to Computed Tomography and Magnetic Resonance Image Segmentation by Almeida, Gonçalo, Tavares, João Manuel R. S.

“…: computed tomography and magnetic resonance. The developed model is fully convolutional with an encoder-decoder structure and high-resolution pathways which can process…”
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