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检索条件"主题词=Encoder-Decoder Architecture"
142 条 记 录,以下是101-110 订阅
排序:
GLD-Net: Improving Monaural Speech Enhancement by Learning Global and Local Dependency Features with GLD Block  23
GLD-Net: Improving Monaural Speech Enhancement by Learning G...
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Interspeech Conference
作者: Xu, Xinmeng Wang, Yang Jia, Jie Chen, Binbin Hao, Jianjun Trinity Coll Dublin Elect & Elect Engn Dublin Ireland Vivo AI Lab Shenzhen Peoples R China Hubei Univ Chinese Med Sch Foreign Languages Wuhan Peoples R China
For monaural speech enhancement, contextual information is important for accurate speech estimation. However, commonly used convolution neural networks (CNNs) are weak in capturing temporal contexts since they only bu... 详细信息
来源: 评论
C-LIENet: A Multi-Context Low-Light Image Enhancement Network
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IEEE ACCESS 2021年 9卷 31053-31064页
作者: Ravirathinam, Praveen Goel, Divyam Ranjani, J. Jennifer Birla Inst Technol & Sci Dept Comp Sci & Informat Syst Pilani 333031 Rajasthan India
Enhancement of low-light images is a challenging task due to the impact of low brightness, low contrast, and high noise. The inability to collect natural labeled data intensifies this problem further. Many researchers... 详细信息
来源: 评论
DP-LinkNet: A convolutional network for historical document image binarization
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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2021年 第5期15卷 1778-1797页
作者: Xiong, Wei Jia, Xiuhong Yang, Dichun Ai, Meihui Li, Lirong Wang, Song Hubei Univ Technol Sch Elect & Elect Engn Wuhan 430068 Hubei Peoples R China Univ South Carolina Dept Comp Sci & Engn Columbia SC 29201 USA
Document image binarization is an important pre-processing step in document analysis and archiving. The state-of-the-art models for document image binarization are variants of encoder-decoder architectures, such as FC... 详细信息
来源: 评论
Deep Learning With Noisy Labels for Spatiotemporal Drought Detection
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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2024年 62卷
作者: Cortes-Andres, Jordi Fernandez-Torres, Miguel-Angel Camps-Valls, Gustau Univ Valencia UV Image Proc Lab IPL Valencia 46980 Paterna Spain
Droughts pose significant challenges for accurate monitoring due to their complex spatiotemporal characteristics. Data-driven machine learning (ML) models have shown promise in detecting extreme events when enough wel... 详细信息
来源: 评论
The exploration of a Temporal Convolutional Network combined with encoder-decoder framework for runoff forecasting
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HYDROLOGY RESEARCH 2020年 第5期51卷 1136-1149页
作者: Lin, Kangling Sheng, Sheng Zhou, Yanlai Liu, Feng Li, Zhiyu Chen, Hua Xu, Chong-Yu Chen, Jie Guo, Shenglian Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China Wuhan Univ Hubei Prov Key Lab Water Syst Sci Sponge City Con Wuhan 430072 Peoples R China Univ Oslo Dept Geosci POB 1047 N-0316 Oslo Norway Wuhan Univ Sch Comp Sci Wuhan 430072 Peoples R China Univ Illinois Dept Geog & Geog Informat Sci Urbana IL 61801 USA
The Temporal Convolutional Network (TCN) and TCN combined with the encoder-decoder architecture (TCN-ED) are proposed to forecast runoff in this study. Both models are trained and tested using the hourly data in the J... 详细信息
来源: 评论
CGFTNet: Content-Guided Frequency Domain Transform Network for Face Super-Resolution
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INFORMATION 2024年 第12期15卷 765-765页
作者: Yekeben, Yeerlan Cheng, Shuli Du, Anyu Xinjiang Univ Sch Comp Sci & Technol Urumqi 830046 Peoples R China
Recent advancements in face super resolution (FSR) have been propelled by deep learning techniques using convolutional neural networks (CNN). However, existing methods still struggle with effectively capturing global ... 详细信息
来源: 评论
A spatiotemporal bidirectional network for video salient object detection using multiscale transfer learning
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INTERNATIONAL JOURNAL OF MULTIMEDIA INFORMATION RETRIEVAL 2024年 第2期13卷 25-25页
作者: Sharma, Gaurav Singh, Maheep NIT Uttarakhand Dept Comp Sci & Engn Srinagar India
Video saliency prediction aims to simulate human visual attention by selecting the most pertinent and important components within a video frame or sequence. When evaluating video saliency, time and space data are esse... 详细信息
来源: 评论
Solving Machine Learning Problems  13
Solving Machine Learning Problems
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13th Asian Conference on Machine Learning (ACML)
作者: Tran, Sunny Krishna, Pranav Pakuwal, Ishan Kafle, Prabhakar Singh, Nikhil Lynch, Jayson Drori, Iddo MIT EECS Cambridge MA 02139 USA MIT Media Lab Cambridge MA 02139 USA Univ Waterloo Waterloo ON Canada
Can a machine learn Machine Learning? This work trains a machine learning model to solve machine learning problems from a University undergraduate level course. We generate a new training set of questions and answers ... 详细信息
来源: 评论
Image to LaTeX with Graph Neural Network for Mathematical Formula Recognition  16th
Image to LaTeX with Graph Neural Network for Mathematical Fo...
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16th IAPR International Conference on Document Analysis and Recognition (ICDAR)
作者: Peng, Shuai Gao, Liangcai Yuan, Ke Tang, Zhi Peking Univ Wangxuan Inst Comp Technol Beijing Peoples R China
Mathematical formula recognition aims to automatically convert formula images into their structured description formats. Recently, some encoder-decoder models have been presented for this task, while they seldom expli... 详细信息
来源: 评论
Multi-scale feature fusion network for pixel-level pavement distress detection
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AUTOMATION IN CONSTRUCTION 2022年 第0期141卷
作者: Zhong, Jingtao Zhu, Junqing Huyan, Ju Ma, Tao Zhang, Weiguang Southeast Univ Sch Transportat Nanjing 211189 Peoples R China
Automatic pavement distress detection is essential to monitoring and maintaining pavement condition. Currently, many deep learning-based methods have been utilized in pavement distress detection. However, distress seg... 详细信息
来源: 评论