Improved Target Detection With YOLOv8 for GAN Augmented Polarimetric Images Using MIRNet Denoising Model

Improved Target Detection With YOLOv8 for GAN Augmented Polarimetric Images Using MIRNet Denoising Model

Polarized images, which record the polarization characteristics of light, are becoming increasingly important in a variety of applications like remote sensing, medical imaging, and target detection. Their ability to offer additional information beyond traditional intensity-based images makes them va...

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Bibliographic Details
Main Authors: Jaydeep Dey, P. Anandan, Sonaa Rajagopal, Muralikrishnan Mani
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Generative adversarial network (GAN)
data augmentation
MIRNet
convolutional neural network (CNN)
polarimetric images
polarization
Online Access:https://ieeexplore.ieee.org/document/10750789/
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https://ieeexplore.ieee.org/document/10750789/

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