Research on Ultrasonic Image Compression in Logging while Drilling: An Asymmetric Convolutional Autoencoder
Author:
Affiliation:
1. University of Electronic Science and Technology of China,School of Automation Engineering
2. Southwest Petroleum University,School of Mechanical Engineering
Funder
China National Offshore Oil Corporation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282627.pdf?arnumber=10282627
Reference13 articles.
1. Multiscale structural similarity for image quality assessment
2. The JPEG still picture compression standard
3. Recalibrating Fully Convolutional Networks With Spatial and Channel “Squeeze and Excitation” Blocks
4. Variable Rate Deep Image Compression With Modulated Autoencoder
5. Optical and Acoustic Fusion in Borehole Imaging Logging
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An Improved UKF Algorithm Based on RBF Neural Network for PEC Response Signal Extraction;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07
2. Hardware-Enabled Compressed Sensing Method for Ultrasonic Images in Logging While Drilling;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07
3. Low-Cost Quantized Compressed Sensing and Transmission Method for Ultrasonic Imaging Logging;IEEE Transactions on Geoscience and Remote Sensing;2024
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