Early Detection of Disease in Tomatoes. Dieser Artikel ist nicht verfügbar.Early Detection of Disease in Tomatoes

Plant diseases and pests are a serious problem in agriculture. Accurate and faster detection of diseases and pests in plants could aid in the development of an early treatment method while significantly lowering economic losses. In this regard, the introduction of deep learning-based image classification has resulted in a significant number of solutions. The primary goal of this research is to detect tomato plant leaf illnesses more quickly by adopting Deep Learning (DL), which can be efficiently utilised for image classification utilising various convolutional neural network (CNN) architectures including VGG-16, ResNet34 and EfficentNet0.Some pre-processing techniques were done on the data before concluding data preparation. An imbalance among the classes was discovered in the dataset, which was remedied using weighted random sample techniques to avoid bias. Model optimization was done to improve perform of the model.The result of the predictions is embedded in an interactive GUI. The GUI allows shows the disease detected. The user may just put their own image for it to detect the class of disease.

Ich beschäftige mich leidenschaftlich mit KI und konzentriere mich auf Projekte, die eine Brücke zwischen Technologie und realen Herausforderungen schlagen. Ich habe ein Deep-Learning-Modell für die Früherkennung von Krankheiten bei Tomatenpflanzen entwickelt und damit das Potenzial von KI in der Landwirtschaft aufgezeigt. Jetzt untersuche ich die Rolle der KI in der Genetik mit dem Ziel, die personalisierte Medizin voranzubringen und die Gesundheitsergebnisse zu verbessern.