note identification

The vegetable recognition was to use image recognition technology to identify different types of vegetables. At present, domestic and foreign research is mainly focused on image recognition algorithms and deep learning technology. Some studies have achieved the recognition of a single fruit or vegetable, but the recognition accuracy and generalization ability still need to be improved. At the same time, the recognition of multiple fruits and vegetables was also a hot and difficult research topic. In recent years, through data augmentation and transfer learning, researchers have tried to solve the problem of insufficient data sets to improve the generalization ability and accuracy of the model. In addition, some vegetable recognition systems based on deep learning had been developed, which could identify vegetables by taking photos or uploading pictures. However, the information given so far did not mention the name or detailed information of the specific vegetable recognition system or algorithm, so it was impossible to provide a more specific answer.

Vegetables identification uses deep learning and machine learning technology to automatically identify the types of vegetables. It could be seen that some research and systems had been developed to realize the identification of vegetables. For example, some researchers used image data sets based on vegetable color and texture to construct a Consecutive neural network model. By adjusting the network layer parameters and using the parameters migration technique, they obtained the preliminary recognition results of vegetables. In addition, there were also systems that used TensorFlow trained Consecutive neural networks and Mobilnet networks based on transfer learning to identify fruits and vegetables with an accuracy of 97%. In addition, some websites and software provided free plant recognition functions that could identify vegetables and other types of plants by uploading pictures or taking photos. These systems use machine learning and big data to improve the accuracy of recognition, and some systems have an accuracy rate of more than 99%. In general, deep learning and machine learning technology could be used to automatically identify vegetables and improve the accuracy and efficiency of identification. However, the specific vegetable recognition system and application still needed further research and development.

The authenticity of Moutai liquor could be identified in many ways. First of all, one could observe the red ribbon on the Moutai bottle. The ribbon of the real wine was bright red, regular, and evenly dyed, while the ribbon of the fake wine was of poor color. Secondly, one could observe the red rubber cap of the Moutai wine. There were red dots on the red rubber cap of the real Moutai wine, while the red dots on the red rubber cap of the fake wine were continuously bright and the printing was blurry. In addition, Moutai's latest anti-counterfeit technology was to place an MRI chip on the red rubber cap, which could be identified by mobile phone sensing. In addition, he could also observe the outer packaging of the Moutai wine. The outer packaging of the real Moutai wine was exquisite, with grooves and three-dimensional feeling, while the outer packaging of the fake wine did not have these characteristics. In addition, one could also identify Moutai by observing the font, the whole body, and the aluminum strip. Finally, consumers could download the official anti-counterfeit tracing system APP of Moutai and use their NFC-enabled mobile phones to conduct independent inquiry and identification. In short, the authenticity of Moutai could be distinguished by observing the streamer, red rubber cap, outer packaging, font, overall, aluminum strip, and the use of anti-counterfeit tracing system.

The identification and classification of vegetables was based on the characteristics and edible organs of vegetables. We can get some information about the classification of vegetables. According to document [2], vegetables could be divided into different categories such as common leafy vegetables, leafy vegetables, fragrant leafy vegetables, and bulbs. Common leafy vegetables were usually marked by fresh and crispy green leaves or leaves, such as cabbage and spinach. Leafy vegetables produce fat leafballs, such as cabbage, lettuce, etc. Spicy leafy vegetables had a spicy taste, such as onions, leeks, celery, and so on. Bulbs are produced from plump pseudostems or lateral buds. In addition, the document [1] also mentioned the classification of vegetables into five categories according to the different temperature requirements of the vegetables. Based on this information, we can identify and classify the vegetables.

There were several vegetable identification apps that he could recommend. One of them was Quick Identification, which integrated a variety of identification tools, including vegetable identification. It could accurately identify pictures of vegetables taken or uploaded in a short period of time and provide detailed information. The other was Cuisine Master. It was a Mini programs that could identify vegetables by taking photos and provide intelligent recommendation services such as the nutritional value of vegetables, taboos, and recipe making. There was also the Omniscient Image, which was a photo recognition product based on AI intelligent image technology. It could recognize more than 20,000 common plants, nearly 8,000 flowers, and nearly 1,000 fruits and vegetables. In addition, there were other vegetable recognition apps, such as AI recognition king, photo recognition, and so on. These apps could help users quickly identify vegetables and provide relevant information and suggestions.

The identification of vegetable seeds can be carried out by observing the shape and characteristics of the seeds. The characteristics of a seed included shape, size, color, surface condition, and smell. The shapes of vegetable seeds could be spherical, oblate, oval, prismatic, shield, heart-shaped, kidney-shaped, lanceolate-shaped, spindle-shaped, irregular, and so on. The size of the seeds was generally divided into three levels: large, medium, and small. The color, appearance, and smell of the seeds could also be used to identify different types of vegetable seeds. However, the specific vegetable seed identification method required further experiments and observations.

There were many ways to identify plants. One way was to use the sweep function of the payment app, open the payment APP, click on the " sweep " in the upper left corner of the homepage, select " identify objects ", and then point the camera at the plant to be identified. After a few seconds, you could get the specific information of the plant. The other method was to use a specialized plant recognition tool, such as the " color " app. Open the software, select the " photo " function, and then take a photo of the plant to be identified. The result would be obtained very quickly. In addition, other plant recognition software or applications could be used to scan the plant or convert the plant's image into a QR code for identification. These methods could help people quickly and accurately identify plants.

The identification of Moutai liquor could be carried out through the following methods. First, it could be identified by the packaging of the wine box. The packaging of the real Moutai was white, and there was the word "Moutai" on it. If the packaging did not have the word Moutai, then it was fake Moutai. Secondly, he could observe the plastic cap of the Moutai wine. The rubber cap of the real Moutai would move slightly if it was twisted left and right, while the rubber cap of the fake Moutai might be pulled off. In addition, he could also observe the anti-counterfeit secret marks on the Moutai bottle, such as the raised printing process on the paper box, miniature text, and so on. In addition, the Moutai official also provided a method for mobile phone NAC verification, which could be verified by downloading the official authentication software and using the mobile phone NAC function. It should be noted that the identification of Moutai liquor could only be carried out by Guizhou Moutai Co., Ltd., and other institutions could not carry out the identification.

The vegetable identification experiment report was an experimental method that aimed to learn and recognize different types of vegetable seeds and seedlings by observing the external shape and internal structure of vegetables, as well as the methods to distinguish them. The experimental materials included dried seeds and germinated seeds of various vegetables, such as radishes, Chinese cabbage, cucumbers, leeks, and so on. The experimental steps involved observing and identifying the characteristics of the leaves and the initial true leaves of the vegetable seedlings, as well as determining the names of various vegetable seedlings based on physical samples. The identification and sprouting experiment report of vegetable seeds also included the records of the seed's shape and characteristics, as well as the methods for determining the seed's sprouting rate and sprouting potential. Through these experiments, one could master the classification and morphological characteristics of vegetable seeds, which would provide a foundation for further study of vegetable cultivation.

" Sweep " was a free plant recognition tool that used the most advanced image recognition technology and artificial intelligence algorithms. With a few simple steps, you can easily identify the plants you are interested in and obtain relevant information. It was very easy to use the " Sweep " function. You only needed to follow the following steps: Step 1: download and install the " Sweep " app. You can search for "scan" in the mobile app store and download it. Step 2: Open the " Sweep " app. He found the 'scan' icon on the phone's desktop and clicked on it. Step 3: Choose the " Plant Identification " function. On the main interface of the " Sweep " APP, you will see various function options. Find " Plant Identification " and click to enter. Step 4: Take photos of the plants. On the plant recognition interface, you can choose to use the camera to take a photo of the plant, or you can choose an existing photo from the phone's photo album. Step 5: Wait for the identification result.