In terms of essence, yes. Both foliar and telial diseases can be detected in plant images using machine learning (ML) or deep learning (a type of AI) for pattern recognition. The specific algorithms used may vary depending on the disease and data, but the overall approach is similar.

• Image Analysis: Both methods analyze digital images of plants for disease signs.
• Pattern Recognition: They learn to identify patterns (color changes, textures) associated with specific diseases.
• Training Data: Both require a large dataset of labeled images (healthy vs. diseased) for training.

Both the terms Artificial Intelligence (AI) and Machine Learning (ML) are related terms because AI is a broad term comprising both machine learning and deep learning a.i ML is a subset of AI. The AI is a discipline that focuses on creating a machine intelligent. It involves the development of algorithms and systems that can give reasons, make differences, learn and make decisions based on the input data. In short, AI helps a system to increase the success rate but not accuracy.

For eg: Siri, chatbots, Robots like Sophia etc.

Whereas, ML is a algorithm in a machine which is programmed to learn on its own without being clearly programmed. In short, it helps a system to learn and increase accuracy but doesn't care about the success of the result instead it will handle the new data more efficiently for various benefits.

For eg: Banking fraud analysis, Google search algorithms, etc.

As mentioned about the detection of foliar diseases, ML detects the disease patterns, colours etc from the dataset based upon tasks and AI helps the ML to recognise the unstructured data for more precise and accurate result with addition to its management practices.