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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Vydané v:	2025 International Conference on Data Science and Business Systems (ICDSBS) s. 1 - 6
Hlavní autori:	Nidhya, R., Pabi, D J Ashpin, Pavithra, Valluru, Poojitha, Vongimalla, Sandeep, S.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 17.04.2025
Predmet:	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
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