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Found 5 papers, 1 papers with code
Tea Chrysanthemum Detection under Unstructured Environments Using the TC-YOLO Model
Tea chrysanthemum detection at its flowering stage is one of the key components for selective chrysanthemum harvesting robot development.
Current and Emergent Economic Impacts of Covid-19 and Brexit on UK Fresh Produce and Horticultural Businesses
This paper describes a study designed to investigate the current and emergent impacts of Covid-19 and Brexit on UK horticultural businesses.
An autoencoder wavelet based deep neural network with attention mechanism for multistep prediction of plant growth
Finally, a recurrent neural network including LSTM and an attention mechanism is proposed for modelling long-term dependencies in the time series data.
Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
Effective plant growth and yield prediction is an essential task for greenhouse growers and for agriculture in general.
Nemesyst: A Hybrid Parallelism Deep Learning-Based Framework Applied for Internet of Things Enabled Food Retailing Refrigeration Systems
Deep Learning has attracted considerable attention across multiple application domains, including computer vision, signal processing and natural language processing.
