AI agriculture enables disease detection, quality grading, and environmental forecasting to boost productivity and resilience.
Use image recognition to detect crop diseases and pests, and provide treatment recommendations to reduce yield loss.
Analyze images and sensor data to assess ripeness and defects, enabling automated grading and improving market competitiveness.
Combine satellite, weather, and sensor data with AI models to predict crop growth, drought, and flood conditions.
This dataset is used to document crop leaf damage to support AI training for crop health monitoring models.
This dataset is used for the automatic recognition of plant pests, containing images of various pests and damages.
This dataset includes images of farmland drought and vegetation recovery, supporting agricultural climate adaptation research.
This dataset combines drought farmland imagery with environmental data for AI-based predictions of irrigation timing and water demand.
This dataset is used for soil crack pattern recognition, aiding agricultural drought research and soil characteristic analysis.
This dataset collects surface images of farmland under different seasons and drought levels for AI monitoring of surface environment changes.
The drought disaster detection dataset is used for AI-supported agricultural monitoring and disaster assessment.
This dataset is used to estimate soil moisture levels based on image data of surface cracking.
The land degradation monitoring dataset records images of varying levels of land cracking and degradation to assist AI in monitoring land quality.
This dataset is used to identify the growth status of crops under drought stress, promoting the development of precision agriculture.
This dataset focuses on the image classification of rural roads, covering various types of roads.
This dataset provides image classification for various types of greenhouses to support intelligent agricultural management.
This dataset provides high-quality image data for the classification of agricultural product stalls, aiding in agricultural intelligence.
The Orchard Vehicle Image Classification Dataset focuses on vehicle type recognition to aid the process of agricultural automation.
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