Ni et al., 2018 - Google Patents
Convolution neural network based automatic corn kernel qualificationNi et al., 2018
View PDF- Document ID
- 14714139403730530458
- Author
- Ni C
- Wang D
- Holmes M
- Vinson R
- Tao Y
- Publication year
- Publication venue
- 2018 ASABE Annual International Meeting
External Links
Snippet
Corn qualification is an important and time-consuming task in biosystem area. The human- based inspection strategy needs to be updated gradually with the quick development of corn industry. In this paper, an automatic corn qualification machine is proposed. Compared to …
- 235000002017 Zea mays subsp mays 0 title abstract description 42
Classifications
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- 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
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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- G—PHYSICS
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- G—PHYSICS
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
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- G—PHYSICS
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- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
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