Enhancing Tensor Based Imputation with CNNS for Astronomical Imagery Data

Satellite imagery frequently contains incomplete or corrupted regions caused by factors such as sensor malfunction, cloud obstruction, or data transmission errors, which adversely affect the accuracy of environmental monitoring and geospatial analysis. This proposed model presents a convolutional ne...

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Bibliographic Details
Published in:	2025 International Conference on Data Science and Business Systems (ICDSBS) pp. 1 - 6
Main Authors:	Nidhya, R., Pabi, D J Ashpin, Pavithra, Valluru, Poojitha, Vongimalla, Sandeep, S.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 17.04.2025
Subjects:	Computational modeling Computer architecture convolutional neural network (CNN) Convolutional neural networks encoder-decoder architecture Image inpainting Image reconstruction Indexes perceptual loss PSNR Real-time systems Remote sensing satellite imagery Satellite images SSIM Tensors VGG16
Online Access:	Get full text
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