Implicit domain adaptation with conditional generative adversarial networks for depth prediction in endoscopy
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-019-01962-w
Abstract: PurposeColorectal cancer is the third most common cancer worldwide, and early therapeutic treatment of precancerous tissue during colonoscopy is crucial for better prognosis and can be curative. Navigation within the colon and comprehensive inspection of… read more here.
Keywords: generative adversarial; conditional generative; implicit domain; model ... See more keywords
A shadow constrained conditional generative adversarial net for SRTM data restoration
Sign Up to like & getrecommendations! Published in 2020 at "Remote Sensing of Environment"
DOI: 10.1016/j.rse.2019.111602
Abstract: Abstract The original data produced by the Shuttle Radar Topography Mission (SRTM) tend to have an abundance of voids in mountainous areas where the elevation measurements are missing. In this paper, deep learning models are… read more here.
Keywords: generative adversarial; shadow constrained; conditional generative; srtm data ... See more keywords
Quantum State Tomography with Conditional Generative Adversarial Networks
Sign Up to like & getrecommendations! Published in 2021 at "Physical review letters"
DOI: 10.1103/physrevlett.127.140502
Abstract: Quantum state tomography (QST) is a challenging task in intermediate-scale quantum devices. Here, we apply conditional generative adversarial networks (CGANs) to QST. In the CGAN framework, two dueling neural networks, a generator and a discriminator,… read more here.
Keywords: quantum state; generative adversarial; conditional generative; state tomography ... See more keywords
Compressed Sensing via Measurement-Conditional Generative Models
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3128721
Abstract: Pre-trained generators have been frequently adopted in compressed sensing (CS) owing to their ability to effectively estimate signals with the prior of NNs. To further refine the NN-based prior, we propose a framework that allows… read more here.
Keywords: conditional generative; sensing via; compressed sensing; via measurement ... See more keywords
Conditional Generative Adversarial Network-Based Tactile Stimulus Generation for Ultrasonic Tactile Display
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3280860
Abstract: Tactile rendering is a promising technology that is necessary to integrate into virtual reality, augmented reality, mixed reality, and even metaverse environments. One of the key technologies for realizing tactile rendering is a reproduction or… read more here.
Keywords: tactile; tactile display; conditional generative; display ... See more keywords
Unsupervised Tumor Characterization via Conditional Generative Adversarial Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2020.2993560
Abstract: Grading for cancer, based upon the degree of cancer differentiation, plays a major role in describing the characteristics and behavior of the cancer and determining treatment plan for patients. The grade is determined by a… read more here.
Keywords: generative adversarial; pathology; conditional generative; cancer ... See more keywords
An ECG Signal Denoising Method Using Conditional Generative Adversarial Net.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2022.3169325
Abstract: In this paper, a novel denoising method for electrocardiogram (ECG) signal is proposed to improve performance and availability under multiple noise cases. The method is based on the framework of conditional generative adversarial network (CGAN),… read more here.
Keywords: ecg signal; denoising method; generative adversarial; conditional generative ... See more keywords
Modeling and Simulation of Sidescan Using Conditional Generative Adversarial Network
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Oceanic Engineering"
DOI: 10.1109/joe.2020.2980456
Abstract: Sidescan sonar has been used for maritime surveys since the mid-20th century. Due to its wide swath coverage and the sharpness of the produced images, it is an invaluable tool still to this day. When… read more here.
Keywords: simulation sidescan; sidescan using; generative adversarial; conditional generative ... See more keywords
SAR Image Ship Object Generation and Classification With Improved Residual Conditional Generative Adversarial Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.3016692
Abstract: Image generation by the conditional generative adversarial network (CGAN) can provide rich samples for supervised classification tasks. However, the unstable gradient updating problem makes it difficult to be used for image generation, especially for the… read more here.
Keywords: network; classification; conditional generative; generation ... See more keywords
Seismic Impedance Inversion Using Conditional Generative Adversarial Network
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3090108
Abstract: Deep-learning methods, such as convolutional neural networks (CNNs), have been successfully applied to seismic impedance inversion in recent years. Compared with traditional geophysical inversion, deep-learning inversion can give inversion results with higher resolution. In this… read more here.
Keywords: generative adversarial; conditional generative; inversion; impedance inversion ... See more keywords
Declutter-GAN: GPR B-Scan Data Clutter Removal Using Conditional Generative Adversarial Nets
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3159788
Abstract: Clutter removal in ground-penetrating radar (GPR) B-scan data has been widely studied in recent years. In this letter, we propose a novel data-driven clutter suppression method in GPR data based on conditional generative adversarial nets… read more here.
Keywords: conditional generative; clutter; method; gpr scan ... See more keywords