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检索条件"任意字段=IEEE-Computer-Society Conference on Computer Vision and Pattern Recognition Workshops"
8947 条 记 录,以下是371-380 订阅
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Cross-dataset Learning for Generalizable Land Use Scene Classification
Cross-dataset Learning for Generalizable Land Use Scene Clas...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Gominski, Dimitri Gouet-Brunet, Valerie Chen, Liming Univ Copenhagen Geog Copenhagen Denmark IGN LaSTIG St Mande France Ecole Cent Lyon LIRIS Ecully France
Few-shot and cross-domain land use scene classification methods propose solutions to classify unseen classes or unseen visual distributions, but are hardly applicable to realworld situations due to restrictive assumpt... 详细信息
来源: 评论
CNLL: A Semi-supervised Approach For Continual Noisy Label Learning
CNLL: A Semi-supervised Approach For Continual Noisy Label L...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Karim, Nazmul Khalid, Umar Esmaeili, Ashkan Rahnavard, Nazanin Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA
The task of continual learning requires careful design of algorithms that can tackle catastrophic forgetting. However, the noisy label, which is inevitable in a real-world scenario, seems to exacerbate the situation. ... 详细信息
来源: 评论
A robust non-blind deblurring method using deep denoiser prior
A robust non-blind deblurring method using deep denoiser pri...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Fang, Yingying Zhang, Hao Wong, Hok Shing Zeng, Tieyong Imperial Coll London London England Chinese Univ Hong Kong Shatin Hong Kong Peoples R China
The existing non-blind deblurring methods are mostly susceptible to noise in the given blurring kernel, which is usually estimated from the observed image. This will produce undesirable ringing artifacts around the re... 详细信息
来源: 评论
Nonuniformly Dehaze Network for Visible Remote Sensing Images
Nonuniformly Dehaze Network for Visible Remote Sensing Image...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chen, Zhaojie Li, Qi Feng, Huajun Xu, Zhihai Chen, Yueting Zhejiang Univ Coll Opt Sci & Engn Hangzhou Peoples R China
Nonuniform haze on remote sensing images degrades image quality and hinders many high-level tasks. In this paper, we propose a Nonuniformly Dehaze Network towards nonuniform haze on visible remote sensing images. To e... 详细信息
来源: 评论
Update Compression for Deep Neural Networks on the Edge
Update Compression for Deep Neural Networks on the Edge
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chen, Bo Bakhshi, Ali Batista, Gustavo Ng, Brian Chin, Tat-Jun Univ Adelaide Adelaide SA Australia Univ New South Wales Sydney NSW Australia
An increasing number of artificial intelligence (AI) applications involve the execution of deep neural networks (DNNs) on edge devices. Many practical reasons motivate the need to update the DNN model on the edge devi... 详细信息
来源: 评论
Semantic Segmentation for Thermal Images: A Comparative Survey
Semantic Segmentation for Thermal Images: A Comparative Surv...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Kutuk, Zulfiye Algan, Gorkem Aselsan Inc Dept Image Proc & Comp Vis Technol Ankara Turkey
Semantic segmentation is a challenging task since it requires excessively more low-level spatial information of the image compared to other computer vision problems. The accuracy of pixel-level classification can be a... 详细信息
来源: 评论
Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems
Adversarial Machine Learning Attacks Against Video Anomaly D...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Mumcu, Furkan Doshi, Keval Yilmaz, Yasin Univ S Florida 4202 E Fowler Ave Tampa FL 33620 USA
Anomaly detection in videos is an important computer vision problem with various applications including automated video surveillance. Although adversarial attacks on image understanding models have been heavily invest... 详细信息
来源: 评论
Continual Learning with Transformers for Image Classification
Continual Learning with Transformers for Image Classificatio...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ermis, Beyza Zappella, Giovanni Wistuba, Martin Rawal, Aditya Archambeau, Cedric AWS Berlin Germany AWS Santa Clara CA USA
In many real-world scenarios, data to train machine learning models become available over time. However, neural network models struggle to continually learn new concepts without forgetting what has been learnt in the ... 详细信息
来源: 评论
Transformaly - Two (Feature Spaces) Are Better Than One
Transformaly - Two (Feature Spaces) Are Better Than One
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cohen, Matan Jacob Avidan, Shai Tel Aviv Univ Blavatnik Sch Comp Sci Tel Aviv Israel Tel Aviv Univ Sch Elect Engn Tel Aviv Israel
Anomaly detection is a well-established research area that seeks to identify samples outside of a predetermined distribution. An anomaly detection pipeline is comprised of two main stages: (1) feature extraction and (... 详细信息
来源: 评论
Self-supervised Learning for Sonar Image Classification
Self-supervised Learning for Sonar Image Classification
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Preciado-Grijalva, Alan Wehbe, Bilal Firvida, Miguel Bande Valdenegro-Toro, Matias German Res Ctr Artificial Intelligence D-28359 Bremen Germany Bonn Rhein Sieg Univ Appl Sci D-53757 St Augustin Germany Univ Groningen Dept AI NL-9747 AG Groningen Netherlands
Self-supervised learning has proved to be a powerful approach to learn image representations without the need of large labeled datasets. For underwater robotics, it is of great interest to design computer vision algor... 详细信息
来源: 评论