Тест, свързан с ръководство · Среден Ниво

AI в теста за диагностика на болести по културите

Тествайте как моделите на изображения, мултиспектралните сензори, вегетационните индекси и данните от полето могат да подпомогнат диагностицирането на болести по културите при реални полеви условия.

Свързани ръководни пътекиAI в диагностиката на болести по културите
Въпрос 1 на 8

What image-classification approach did Mohanty et al. evaluate on the PlantVillage leaf-image dataset?

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Отговорите и обясненията се появяват, докато отговаряте на теста.

  1. What image-classification approach did Mohanty et al. evaluate on the PlantVillage leaf-image dataset?
    • A convolutional neural network trained to classify crop-disease images
    • A satellite-only weather forecast model
    • A recurrent speech recognition network
    • A hand-written treatment rule with no image input
  2. In a multispectral study of gray mold in tomato leaves, why was near-infrared reflectance measured?
    • To measure the temperature of the soil beneath each leaf
    • To test whether spectral changes could be observed before visible symptoms
    • To identify the plant species from its roots
    • To replace all disease labels with weather forecasts
  3. What does NDVI indicate when computed from red and near-infrared reflectance?
    • A definitive diagnosis of a particular plant disease
    • The exact amount of pesticide needed
    • A vegetation greenness or condition signal
    • The number of pathogens in a leaf
  4. What does domain shift mean for a crop-image model?
    • The model automatically changes the target crop
    • Images receive different file names
    • A disease moves from root to leaf
    • Training and deployment data differ in distribution, which can change model performance
  5. What potential benefit can transfer learning offer when labeled crop images are limited?
    • A pretrained model may provide useful features to adapt to the target task
    • It guarantees better results for any crop and disease
    • It removes the need for field validation
    • It makes training data unnecessary
  6. Приблизително какъв дял от световните добиви на култури се губи от вредители и болести всяка година?
    • по-малко от 1%
    • Около 20-40%
    • точно 5%
    • над 90%
  7. How many controlled-condition leaf images did the PlantVillage paper use?
    • 54,306 images
    • 5,430 images
    • 543 images
    • 540,306 images
  8. How is NDVI calculated from near-infrared and red reflectance?
    • (NIR + red) ÷ (NIR − red)
    • NIR × red
    • NIR − red without normalization
    • (NIR − red) ÷ (NIR + red)