The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …

Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …

Deep learning has emerged as a potential tool for crop yield prediction, allowing the model
to automatically extract features and learn from the datasets. Meanwhile, smart farming …

The art of predicting crop production is done before the crop is harvested. Crop output
forecasts will help people make timely judgments concerning food policy, prices in markets …

Global agricultural production, in particular, is of increasing concern to the major
international organizations in charge of nutrition. The rising demand for food globally due to …

Abstract Crop Recommendation Systems are invaluable tools for farmers, assisting them in
making informed decisions about crop selection to optimize yields. These systems leverage …

Crop growth condition and production play an important role in food management and
economic development. Therefore, estimating yield accurately and timely is of vital …

Accurate and timely crop yield estimation is crucial for crop market planning and food
security. Combining remotely sensed big data with deep learning for yield estimation has …

Yield prediction is essential in food security, food trade, and field management. However,
due to the associated complex formation mechanisms of yield, accurate and timely yield …

Agriculture faces a significant challenge in predicting crop yields, a critical aspect of decision-
making at international, regional, and local levels. Crop yield prediction utilizes soil, climatic …