Search Results for author:
Found 17 papers, 5 papers with code
AE-RED: A Hyperspectral Unmixing Framework Powered by Deep Autoencoder and Regularization by Denoising
In this way, both the characteristics of the deep autoencoder based unmixing methods and priors provided by denoisers are merged into our well-designed framework to enhance the unmixing performance.
Guided Deep Generative Model-based Spatial Regularization for Multiband Imaging Inverse Problems
More precisely, the regularization is conceived as a deep generative network able to encode spatial semantic features contained in this auxiliary image of high spatial resolution.
ControlVideo: Conditional Control for One-shot Text-driven Video Editing and Beyond
This paper presents \emph{ControlVideo} for text-driven video editing -- generating a video that aligns with a given text while preserving the structure of the source video.
Equivariant Energy-Guided SDE for Inverse Molecular Design
Inverse molecular design is critical in material science and drug discovery, where the generated molecules should satisfy certain desirable properties.
Automatic reorientation by deep learning to generate short axis SPECT myocardial perfusion images
Five-fold cross-validation with 180 stress and 201 rest MPIs was used for training and internal validation; the remaining images were used for testing.
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations
Further, we provide an alternative explanation of the EGSDE as a product of experts, where each of the three experts (corresponding to the SDE and two feature extractors) solely contributes to faithfulness or realism.
Ranked #1 on
Image-to-Image Translation
on AFHQ (Wild to Dog)
Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing
Spectral unmixing is one of the most important quantitative analysis tasks in hyperspectral data processing.
A Concept Knowledge-Driven Keywords Retrieval Framework for Sponsored Search
This framework has been successfully applied to Baidu's sponsored search system, which yields a significant improvement in revenue.
A Plug-and-Play Priors Framework for Hyperspectral Unmixing
Spectral unmixing is a widely used technique in hyperspectral image processing and analysis.
Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors
In our work, we propose an NMF based unmixing framework which jointly uses a handcrafting regularizer and a learnt regularizer from data.
Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning
A mobile app interface usually consists of a set of user interface modules.
Generative Adversarial Networks For Data Scarcity Industrial Positron Images With Attention
In the industrial field, the positron annihilation is not affected by complex environment, and the gamma-ray photon penetration is strong, so the nondestructive detection of industrial parts can be realized.
Hyperspectral Unmixing via Deep Autoencoder Networks for a Generalized Linear-Mixture/Nonlinear-Fluctuation Model
This paper presents an unsupervised nonlinear spectral unmixing method based on a deep autoencoder network that applies to a generalized linear-mixture/nonlinear fluctuation model, consisting of a linear mixture component and an additive nonlinear mixture component that depends on both endmembers and abundances.
A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation
To the best of our knowledge, this dataset is the first publicly available dataset created in a systematic manner with ground-truth for spectral unmixing.
Classification of entities via their descriptive sentences
Hypernym identification of open-domain entities is crucial for taxonomy construction as well as many higher-level applications.
Constructing a Hierarchical User Interest Structure based on User Profiles
In this study, we constructed the user interest hierarchy via user profiles.
Understanding Humans' Strategies in Maze Solving
Navigating through a visual maze relies on the strategic use of eye movements to select and identify the route.
