• Mudugula Babu
• Talla Umesh
• Dr. Sreenivas Mekala

In this paper author is predicting ficus plant growth/crop yield by evaluating performance of various machine learning algorithms such as SVR (Support Vector Regression), Random Forest Regression (RF) and LSTM (Long Short Term Memory) deep neural network algorithm. SVR and RF are the traditional old algorithms whose performance of prediction will be low due to unavailable of deep learning technique. To overcome from this problem author is using LSTM deep neural network algorithm to predict plant growth.

Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments

"Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.g107-g114, June-2022, Available :http://www.jetir.org/papers/JETIR2206616.pdf

"Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppg107-g114, June-2022, Available at : http://www.jetir.org/papers/JETIR2206616.pdf