What is Image Annotation in Agriculture?

What is Image Annotation in Agriculture?

Annotation services for images are becoming more important due to the advancement in computer vision-based AI models for new fields. This cutting-edge technology is essential for agriculture to increase crop yields and productivity while reducing costs.

Image annotation is actually the best technique to make objects easily recognizable by machines using deep learning algorithms. Image annotation is used in agriculture to identify crops and other objects so that machines can make the correct decisions without humans. Let’s now see what image annotation can do in agricultural fields and how machine learning and artificial intelligence can use it.

Identifying the Fruits/Crops/Vegetables

Robots used agriculture and growing to identify crops, including fruits and vegetables, for various tasks. Images can be annotated to identify the crops for machine learning models such as drones and robots.

Annotation to Check Plants’ Fructification

Image annotation is similar to detecting crops. It can also be used to check the fructification level of plants and determine if they are ready for harvesting. The image annotation technique can detect these plants and notify farmers about the Fructification levels.

Crops Health Monitoring

Image annotation is used to detect the crops and also aids in the development of deep learning AI models that can be trained to create computer vision models. Robots can monitor the condition of the crop or plant closely and determine if it is infected, mature, or not.

Live Stock Management

AI-enabled devices can also manage part of the agricultural sector, which includes animal husbandry. Image annotation is a way to identify and recognize animals, allowing farmers to keep an eye on livestock and monitor it. This makes animal husbandry more profitable. The polygon and bounding box annotations help to identify the animals accurately.

Annotation for Geosensing

Image annotation is also used in the agricultural sector for geo-sensing. This allows you to assess the conditions of the fields and determine the best time to sow and harvest crops. Drones are used, and the semantic segmentation image annotation technique is used to monitor and observe the health conditions of various agricultural fields.

Annotation to Detect Unwanted Crops

There are many undesirable crops that can be grown alongside useful crops. These crops use the soil minerals under the roots and should eventually reach the main crop. These unwanted plants are known as weeds and should be eradicated to increase crop yield and improve productivity across the entire agricultural field.

Labelify offers the image annotation service to agricultural and farming. This allows livestock and crops to be recognized by drones and robots using computer vision. It provides high-quality training data sets to machine learning models for different fields, including agriculture. Analytics works with highly-skilled annotations to annotate images of the highest quality so that the AI model can accurately detect and recognize objects in real-life.