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Zeng et al., 2023 - Google Patents

Lightweight tomato real-time detection method based on improved YOLO and mobile deployment

Zeng et al., 2023

Document ID
10845350604675451679
Author
Zeng T
Li S
Song Q
Zhong F
Wei X
Publication year
Publication venue
Computers and electronics in agriculture

External Links

Snippet

The current deep-learning-based tomato target detection algorithm has many parameters; it has drawbacks of large computation, long time consumption, and reliance on high- computing-power devices such as graphics processing units (GPU). In this study, we …
Continue reading at www.sciencedirect.com (other versions)

Classifications

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    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6256Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
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    • GPHYSICS
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    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
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