https://towardsdatascience.com/image-data-labelling-and-annotation-everything-you-need-to-know-86ede6c684b1
https://lionbridge.ai/articles/image-annotation-tools-for-computer-vision/
I think this will helpful for you
Nowadays, The wide adaptation of (Generative Adversarial Network)GAN has gained the attraction of researchers in the Single Image Super-Resolution (SISR) image. With the help of this model and the SISR concept, you will be generated data in different resolutions and used in data set annotation.
For e.g, in face alteration and face aging.
Extended work in GAN in natural-looking face image generation by the state-of-the-art models:
StyleGAN, StyleGAN2, StyleFlow.
Face aging and face alteration is the best example of face data annotation by considering the age or pose variant attribute.
For face aging, quantitative results in the below mentioned paper:
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9211009
it depends on image type, if it's about medical imaging, you can use SPM
https://www.fil.ion.ucl.ac.uk/spm/
It's a good software package with different applications and analysis of medical imaging.
Dear Geetika Jain Saxena
Please check this article
Article Novel Feature Selection and Voting Classifier Algorithms for...
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