Results 41 to 50 of about 5,326,339 (296)
Image Quality Predictor with Highly Efficient Fully Convolutional Neural Network
Advances in Multimedia, 2022 A highly efficient deep fully convolutional neural network (DFCN) for image quality assessment (IQA) is designed in this paper. The DFCN consists of two branches, one scoring local patches and the other estimating the weights of local patches to enhance ...
Cao Yu-Dong, Liao Xin-Lin, Liu Hai-Yan
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Texture segmentation with Fully Convolutional Networks
CoRR, 2017 In the last decade, deep learning has contributed to advances in a wide range computer vision tasks including texture analysis. This paper explores a new approach for texture segmentation using deep convolutional neural networks, sharing important ideas with classic filter bank based texture segmentation methods.
Vincent Andrearczyk, Paul F. Whelan
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Deeper and wider fully convolutional network coupled with conditional random fields for scene labeling [PDF]
, 2016 Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning.
Nguyen Thanh, Kien +5 more
core +1 more source
LSTM Fully Convolutional Networks for Time Series Classification
IEEE Access, 2018 Fully convolutional neural networks (FCNs) have been shown to achieve the state-of-the-art performance on the task of classifying time series sequences.
Fazle Karim +3 more
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Fully Convolutional Network for Melanoma Diagnostics
CoRR, 2018 This work seeks to determine how modern machine learning techniques may be applied to the previously unexplored topic of melanoma diagnostics using digital pathology. We curated a new dataset of 50 patient cases of cutaneous melanoma using digital pathology.
Adon Phillips +2 more
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Fully-Convolutional Siamese Networks for Object Tracking [PDF]
, 2016 The first two authors contributed equally, and are listed in alphabetical order.
Luca Bertinetto +4 more
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Shelf Commodity Identification Method Based on Hybrid Fully Convolutional Automatic Encoder
IEEE Access, 2019 At present, the semantic information segmentation algorithms mainly include FCN (Fully Convolutional Network), PSPNet (Pyramid Scene Parsing Network), Deeplab and so on. In view of the inadequate results of features extracted by these algorithms from RGB
Aofeng Cheng, Guodong Chen, Zheng Wang
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A two‐scaled fully convolutional learning network for road detection
IET Image Processing, 2022 This paper aims to detect road regions based on a two‐scaled deep neural network. The information from different scales is helpful to boost the performance of deep learning models, and it is also a widely used strategy in various computer vision ...
Dingding Yu, Xianliang Hu, Kewei Liang
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Fully-parallel Convolutional Neural Network Hardware
CoRR, 2020 8 pages, 6 figures, to be submitted to an IEEE ...
Christiam F. Frasser +5 more
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A Fully Convolutional Neural Network for Speech Enhancement [PDF]
Interspeech 2017, 2017 In hearing aids, the presence of babble noise degrades hearing intelligibility of human speech greatly. However, removing the babble without creating artifacts in human speech is a challenging task in a low SNR environment. Here, we sought to solve the problem by finding a `mapping' between noisy speech spectra and clean speech spectra via supervised ...
Se Rim Park, Jinwon Lee
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