Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Yogesh H. Dandawate"'
Publikováno v:
Multimedia Tools and Applications. 81:31145-31160
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::671270fa1b9d0fc3b335d686422ef932
https://doi.org/10.1007/s11042-022-12983-0
https://doi.org/10.1007/s11042-022-12983-0
Publikováno v:
Computational Intelligence in Image and Video Processing ISBN: 9781003218111
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::190e1e60ee0d125517751d2b7c502cfe
https://doi.org/10.1201/9781003218111-5
https://doi.org/10.1201/9781003218111-5
Autor:
Radhika Bhagwat, Yogesh H. Dandawate
Publikováno v:
International Journal of Engineering and Technology Innovation. 11:251-264
Plant diseases cause major yield and economic losses. To detect plant disease at early stages, selecting appropriate techniques is imperative as it affects the cost, diagnosis time, and accuracy. This research gives a comprehensive review of various
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::584f88a1e38b9426016ff670c1e9bf87
https://doi.org/10.46604/ijeti.2021.8244
https://doi.org/10.46604/ijeti.2021.8244
Autor:
Radhika Bhagwat, Yogesh H. Dandawate
Publikováno v:
International Journal of Engineering and Technology Innovation. 11:216-228
Crop disease detection methods vary from traditional machine learning, which uses Hand-Crafted Features (HCF) to the current deep learning techniques that utilize deep features. In this study, a hybrid framework is designed for crop disease detection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::472af809d0e11268c2fc5c9bc572300d
https://doi.org/10.46604/ijeti.2021.7346
https://doi.org/10.46604/ijeti.2021.7346
Convolutional neural network-based feature extraction using multimodal for high security application
Autor:
Yogesh H. Dandawate, Priti Shende
Publikováno v:
Evolutionary Intelligence. 14:1023-1033
An efficient biometrics-based security system is the prime need in modern security industry. Biometric modalities are unique features of any human being based on which a computer system can recognise, authenticate or verify a person. In this paper we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3db461c9b22e281537b420037f74445
https://doi.org/10.1007/s12065-020-00522-5
https://doi.org/10.1007/s12065-020-00522-5
Publikováno v:
2021 2nd Global Conference for Advancement in Technology (GCAT).
Sales forecasting is an important aspect of modern market intelligence. A reliable revenue forecast will help a company preserve capital on unnecessary product, prepare better for the future, and increase profit. The estimation of grocery sales is as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c696f7850616351244aa17769fa648d
https://doi.org/10.1109/gcat52182.2021.9587668
https://doi.org/10.1109/gcat52182.2021.9587668
Publikováno v:
Multimedia Tools and Applications. 79:2109-2125
This paper presents a fusion featured metric for no-reference image quality assessment of natural images. Natural images exhibit strong statistical properties across the visual contents such as leading edge, high dimensional singularity, scale invari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d89e799c30031a387605ebf9b1a180c
https://doi.org/10.1007/s11042-019-08217-5
https://doi.org/10.1007/s11042-019-08217-5
Publikováno v:
Malaysian Journal of Computer Science. 32:31-46
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fee968882c06fa1446a58d1eb872c761
https://doi.org/10.22452/mjcs.vol32no1.3
https://doi.org/10.22452/mjcs.vol32no1.3
Publikováno v:
2021 6th International Conference for Convergence in Technology (I2CT).
Popular and widely used JPEG images suffer from blocking artifact. Blocking artifact degrades the quality of an image. No Reference Image Quality Assessment (NRIQA) metric using block based features are designed in this paper. Artificial Neural Netwo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ce971cfdcc394d988a5be9041d3c47a
https://doi.org/10.1109/i2ct51068.2021.9417905
https://doi.org/10.1109/i2ct51068.2021.9417905