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Keyword: Super-resolution
Object Classifications by Image Super-Resolution Preprocessing for Convolutional Neural Networks
Blurred small objects produced by cropping, warping, or intrinsically so, are challenging to detect and classify. Therefore, much recent research is focused on feature extraction built on Faster R-CNN and follow-up systems. In particular, RPN, SPP, FPN, SSD, and DSSD are the layered feature extraction methods for multiple object detections and small objects. However, super-resolution…
Read More Super Resolution Based Underwater Image Enhancement by Illumination Adjustment and Color Correction with Fusion Technique
In underwater photographs are look like low-quality images, the main reason is behind that due to attenuation of the propagated light, absorption and scattering effect. The absorption significantly reduces the light energy, while the dispersion causes changes in the light propagation path. They result in foggy appearance and degradation of contrast, causing misty distant objects.…
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