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- Title
Attention-Based Multiscale Feature Pyramid Network for Corn Pest Detection under Wild Environment.
- Authors
Kang, Chenrui; Jiao, Lin; Wang, Rujing; Liu, Zhigui; Du, Jianming; Hu, Haiying
- Abstract
Thus, the I precision i and I recall i can be calculated using: (5) HT <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mi>r</mi><mi>e</mi><mi>c</mi><mi>i</mi><mi>s</mi><mi>i</mi><mi>o</mi><mi>n</mi><mo>=</mo><mfrac><mrow><mo>#</mo><mi>T</mi><mi>P</mi></mrow><mrow><mo>#</mo><mi>T</mi><mi>P</mi><mo>+</mo><mo>#</mo><mi>F</mi><mi>P</mi></mrow></mfrac></mrow></semantics></math> ht (6) HT <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>r</mi><mi>e</mi><mi>c</mi><mi>a</mi><mi>l</mi><mi>l</mi><mo>=</mo><mfrac><mrow><mo>#</mo><mi>T</mi><mi>P</mi></mrow><mrow><mi>G</mi><mi>T</mi></mrow></mfrac></mrow></semantics></math> ht where HT <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>#</mo><mi>T</mi><mi>P</mi></mrow></semantics></math> ht and HT <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>#</mo><mi>F</mi><mi>P</mi></mrow></semantics></math> ht represent the number of detected and misdetected corn pests, respectively. Thus, there are different HT <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi> </mi><mi>s</mi></msub></mrow></semantics></math> ht in our AMFFP-Net module. First, the I IoU i is used to verify the overlap between the ground-truth and predicted bounding box, which can be defined: (4) HT <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>I</mi><mi>o</mi><mi>U</mi><mo>=</mo><mfrac><mrow><mi>a</mi><mi>r</mi><mi>e</mi><mi>a</mi><mo stretchy="false">(</mo><mi>G</mi><mo> </mo><mi>P</mi><mo stretchy="false">)</mo></mrow><mrow><mi>a</mi><mi>r</mi><mi>e</mi><mi>a</mi><mo stretchy="false">(</mo><mi>G</mi><mo> </mo><mi>P</mi><mo stretchy="false">)</mo></mrow></mfrac></mrow></semantics></math> ht where I G i and I P i denote the ground truth and predicted bounding box, respectively.
- Subjects
CORN pests; DEEP learning; IMAGE recognition (Computer vision); PATTERN recognition systems; PYRAMIDS; OBJECT recognition (Computer vision); RICE diseases &; pests
- Publication
Insects (2075-4450), 2022, Vol 13, Issue 11, p978
- ISSN
2075-4450
- Publication type
Article
- DOI
10.3390/insects13110978