Maria et al., 2022 - Google Patents
Cauliflower disease recognition using machine learning and transfer learningMaria et al., 2022
- Document ID
- 15260351962176918194
- Author
- Maria S
- Taki S
- Mia M
- Biswas A
- Majumder A
- Hasan F
- Publication year
- Publication venue
- Smart Systems: Innovations in Computing: Proceedings of SSIC 2021
External Links
Snippet
In terms of overall winter cropping area and production in Bangladesh, cauliflower dominates a large share. It has many health benefits like decrease the risk of obesity, diabetes, and heart disease. It is a cultivated and winter crop which has huge demand in the …
- 201000010099 disease 0 title abstract description 67
Classifications
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06K9/6256—Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
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- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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- G—PHYSICS
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