High-Performance Deep learning to Detection and Tracking Tomato Plant Leaf Predict Disease and Expert Systems

Nowadays, technology and computer science are rapidly developing many tools algorithms, especially in the field of artificial intelligence. Machine learning is involved development new methodologies models that have become a novel machine area applications for In addition to architectures conventional neural network methodologies, deep refers use which include multiple processing layers.
 this paper, Convolutional were designed detect (diagnose) plant disorders by applying samples healthy unhealthy images analyzed means methods learning. The trained using an open data set containing (18,000) ten different plants, including plants. Several model been achieve best performance (97 percent) when respectively [plant, disease] paired detected. This very useful information or early warning technique method can be further improved with substantially high-performance rate support automated disease detection system work actual farm conditions.