How to use Computer Vision in Agriculture?

Computer vision is the ability of a computer to understand its environment by analyzing the images it captures. It has applications in many industries such as agriculture, manufacturing.

In agriculture, computer vision is used for tasks such as crop classification, disease detection, pest identification, and weed recognition. This article will focus on some of the most common uses for computer vision in agriculture, such as detecting diseases and monitoring crop yields. This technology has been rapidly deployed in the agricultural sector in recent years because it can be used to increase the yield of crops by 20% or more in areas that are experiencing drought conditions.

In manufacturing, computer vision is used for quality control by detecting defects on manufactured products like clothes or food items. Computer vision can also be used for sorting tasks like detecting defective pieces of metal or plastic from a production line and then segregating them from good pieces It works by recognizing the features and properties of objects in the camera’s field of view and then determining their position, size, shape, color or other properties. As computer vision technology becomes more advanced and affordable, it is being used more and more frequently in homes as well as industry.

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  • Naveen Pandey Data Scientist Machine Learning Engineer

    Naveen Pandey has more than 2 years of experience in data science and machine learning. He is an experienced Machine Learning Engineer with a strong background in data analysis, natural language processing, and machine learning. Holding a Bachelor of Science in Information Technology from Sikkim Manipal University, he excels in leveraging cutting-edge technologies such as Large Language Models (LLMs), TensorFlow, PyTorch, and Hugging Face to develop innovative solutions.

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