Cargando…
Blind First-Order Perspective Distortion Correction Using Parallel Convolutional Neural Networks
In this work, we present a network architecture with parallel convolutional neural networks (CNN) for removing perspective distortion in images. While other works generate corrected images through the use of generative adversarial networks or encoder-decoder networks, we propose a method wherein thr...
Autores principales: | Del Gallego, Neil Patrick, Ilao, Joel, Cordel, Macario |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506918/ https://www.ncbi.nlm.nih.gov/pubmed/32872565 http://dx.doi.org/10.3390/s20174898 |
Ejemplares similares
-
Automatic Tumor Segmentation With a Convolutional Neural Network in Multiparametric MRI: Influence of Distortion Correction
por: Bielak, Lars, et al.
Publicado: (2019) -
Introducing Swish and Parallelized Blind Removal Improves the Performance of a Convolutional Neural Network in Denoising MR Images
por: Sugai, Taro, et al.
Publicado: (2021) -
Parallel Adaptation to Spatially Distinct Distortions
por: Sauer, Yannick, et al.
Publicado: (2020) -
Face Distortion Aftereffects Evoked by Featureless First-Order Stimulus Configurations
por: Vakli, Pál, et al.
Publicado: (2012) -
Architectural Distortion-Based Digital Mammograms Classification Using Depth Wise Convolutional Neural Network
por: Rehman, Khalil ur, et al.
Publicado: (2021)