Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and human language. NLP has gained a lot of traction in recent years due to the rise of chatbots, virtual assistants, and voice-enabled devices. In this post, we'll explore NLP in more detail and its applications. What is NLP? NLP is a branch of AI that deals with the processing and analysis of natural language, such as speech or text. It involves the use of algorithms to enable computers to understand, interpret, and generate human language. NLP is an interdisciplinary field that draws on computer science, linguistics, and cognitive psychology. Applications of NLP Chatbots and Virtual Assistants One of the most common applications of NLP is in chatbots and virtual assistants. NLP algorithms enable these systems to understand and interpret human language and respond appropriately. This technology is being used in customer service, healthcare, and e-comme...
Introduction
Mangoes have been a crucial commodity in global import and export, but in recent years, the industry has experienced a decline due to the prevalence of mango tree disease. The loss of mango yield has been a cause for concern among producers, and finding a way to combat the disease has become a top priority. In response to this problem, a new approach has been proposed, which involves using computer vision to detect and diagnose the health of mango leaves.
Creating the Mango Leaf Health Detection Dataset
The proposed approach involves creating a "Mango Leaf Health Detection Dataset" that uses intelligent computer vision algorithms. This dataset was tested and validated using YOLO v5s, YOLO v7, and YOLO v8s.
The YOLO Algorithm
The YOLO algorithm analyzes images of the mango leaves by passing them through a pipeline that redefines the image in grid cells, constructs bounding boxes, and predicts the class of the leaf. This method not only saves time but also delivers accurate and effective results, allowing producers to target the exact area where pesticides are needed.
Novel Custom-made Dataset
The Mango Leaf Health Dataset is a novel custom-made dataset that includes diverse sets of mango leaves captured through different modes. The main motivation behind this approach was to redefine and restructure the traditional and previous methods used for disease detection in mango leaves and introduce a more efficient and fast way.
Training and Testing the Dataset
The approach was tested by training the dataset on YOLO v5s, YOLO v7, and YOLO v8s models. YOLO v7 outperformed the other two deep learning models in terms of training parameters and the number of layers, achieving better results.
Innovation and Future Advancements
However, there is still room for innovation in the proposed system. One potential innovation would be to create an end-to-end model that provides dual validation by combining a detection model with a classification one, allowing for the identification of a wider range of agricultural crop diseases.
Detection on Drone Footage
You can watch a video below featuring the detection of our model on drone footage taken in a mango orchard.
Conclusion
Overall, the proposed approach using computer vision and the Mango Leaf Health Dataset has the potential to revolutionize the way mango trees are treated for disease, saving time and resources and ultimately increasing yields. The innovation in this field is ongoing, and it is exciting to see what other advances will be made in the future.
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