INSTITUTIONAL DIGITAL REPOSITORY

Browsing Year-2020 by Subject "Deep learning"

Browsing Year-2020 by Subject "Deep learning"

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  • Chauhan, J.; Goyal, P. (2021-07-28)
    Background and objective: Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. ...
  • Dudhane, A.; Hambarde, P.; Patil, P.; Murala, S. (2021-07-01)
    Underwater image restoration is a challenging problem due to the multiple distortions. Degradation in the information is mainly due to the 1) light scattering effect 2) wavelength dependent color attenuation and 3) object ...
  • Orlando, J.I.; Fu, H.; Breda, J.B.; Keer, K.; Bathula, D.R.; Diaz-Pinto, A.; Fang, R.; Heng, P.; Kim, J.; Lee, J.; Lee, J.; Li, X.; Liu, P.; Lu, S.; Murugesan, B.; Naranjo, V.; Phaye, S.S.R.; Shankaranarayana, S.M.; Son, J.; Hengel, A.V.D.; Wang, S.; Wu, J.; Wu, Z.; Xu, G.; Xu, Y.; Yin, P.; Li, F.; Zhang, X.; Xu, Y.; Bogunovi ´c, H. (2020-03-17)
    Glaucoma is one of the leading causes of irreversible but preventable blindness in working age popula- tions. Color fundus photography (CFP) is the most cost-effective imaging modality to screen for retinal disorders. ...
  • Nema, S.; Dudhane, A.; Murala, S.; Naidu, S. (2020-03-13)
    Even with proper acquisition of brain tumor images, the accurate and reliable segmentation of tumors in brain is a complicated job. Automatic segmentation become possible with development of deep learning algorithms that ...

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