With the advancement of computer technology, artificial intelligence technology represented by image recognition has developed rapidly and has been widely used in aviation, medicine and other fields. Today, image recognition technology has also become an indispensable part of the development of modern agriculture, and an important technical force for the realization of agricultural informatization and automation. At present, image recognition technology is widely used in agricultural production, natural resource analysis, weather forecasting, environmental monitoring, disease and pest monitoring and early warning, and many other agricultural scenes. It is important for strengthening crop production management, accurately forecasting crop yields, optimizing the pattern of planting space, and further exploiting the potential of agricultural production. It is of great significance. Wheat is one of the main food crops in my country, and the output of wheat will have a direct impact on my country's food security. As the most basic factor of the three elements of wheat yield, the number of ears per mu is very decisive for yield. An important step in estimating the production and yield of wheat is to obtain the value of ears per mu. At present, the traditional artificial field survey method is time-consuming, laborious, and subjective, and lacks a unified wheat ear counting standard. To this end, Top Yunnong independently developed a wheat ear number measurement system per mu , specifically for measuring the number of wheat ears per mu. The system collects wheat image information in a specific area and uses artificial intelligence technologies such as deep learning and image recognition to perform image segmentation. , Image enhancement and other operations, extract the information of wheat ears, quickly calculate the number of wheat ears per mu, and can store the data, which is of great significance to the high-yield cultivation of wheat and the breeding of improved varieties. The wheat ear count measurement system can be widely used in scientific research institutions and social units such as agricultural science academies, schools, breeding companies, seed stations, etc. Top Yunnong independently develops online APP through the integrated system, and users only need a few simple operations, namely Earlier information on wheat yield can be obtained, and the measurement results are not only fast but also accurate, providing practical value for crop monitoring and optimal decision-making in the process of wheat production. By uploading a specific range of wheat pictures, the APP can use artificial intelligence technology to automatically detect the number of wheat ears and the number of ears per mu. It also supports batch detection and analysis of multiple photos, and automatically generates reports, effectively realizing data editing, screening, exporting and sharing Features. With the in-depth development of agricultural science and technology, image recognition technology is accelerating the integration of other artificial intelligence technologies to jointly promote the development of agricultural production and other links in the direction of convenience and intelligence. Top Yunnong will also adopt "Internet of Things + Artificial Intelligence". "Technology is the core, continue to strengthen the exploration and application of technology, accelerate the transformation of technological achievements, and actively promote the intelligent development of the agricultural field!
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How to measure the number of ears per mu of wheat? The measurement system of the number of ears per mu of wheat can easily realize the rapid speed of ears per mu..