Image annotation is becoming important for computer vision based all types of AI models developed through machine learning. In agriculture sector AI has set foot through various advance equipment system and techniques, making this field more productive and efficient.
Yes, robotics, drones and AI-enabled machines are dedicatedly used in agricultural sector for performing various tasks. Actually, all these machines works on computer vision based technology. And these AI-enabled machines are trained through training data sets generated through images annotation.
Image Annotation for AI and Machine Learning
Image annotation is the data labeling technique used to make the varied objects recognizable for machines. And in machine learning huge amount of such datasets are used through algorithms. Hence, image annotation plays an important role in model development.
And computer vision based all types of AI model can be well-trained if high-quality datasets is used with right algorithm. Though, there are varied types of image annotation techniques and according to the model’s algorithm’s compatibility and other feasibility, images are annotated.
IMAGE ANNOTATION IN AGRICULTURE
When image annotation is done for agriculture sector, there are many things (object of interest) are annotated as per the model requirement. From plants to fruit or land everything is annotated to make them recognizable or even comprehensible for machines so that they can actions accordingly. So, right here below we will discuss why and how image annotation in agriculture or farming.
Image Annotation for Robotics to Detect Crops
The crops, plants or floras need to be detectable to robots for picking the fruits and vegetables. For precise detection of such objects, precise annotation is also important, so image annotation using the bounding box technique can annotate the object making AI possible in agriculture.
Image Annotation to Detect the Unwanted Crops
Along with useful plants, unwanted crops also grew while cultivating the fields in the agricultural sector. Weeds, wildflowers and other wild plants are highlighted with image annotation technique to make it identifiable, so that it can be removed by the machine for better growth and yield of the crop.
And when huge amount of annotated images are used to train the model, then robots become capable to detect such unwanted crops that are eating nutrition of the main crops.
Image Annotation to Monitor the Health of Crops
Crops matured, not matured or getting infected due to insects or fungus can be now monitored through AI-enabled devices like drones or robots. But again to make such things identifiable you need to use the image annotation technique. From semantic segmentation to other popular image annotation techniques, there are many procedures that help to monitor the health of the crop.
Image Annotation for Geo Sensing of Fields
The one of the most important yet crucial use of image annotation is identifying the soil condition and health of the field. Yes, image annotation can be used for geo sensing that helps to find out the condition of agricultural field and make the right decision of cultivation or harvesting. The semantic image segmentation helps to generate set of large data for deep learning in agro field.
Anolytics is the leading image annotation service provider in the industry. It is also offering the high-quality image annotation service for agricultural field. AI companies seeking for high-quality training data for the robots, drone and other autonomous machines can get the annotated images here with scalable solution to produce the large volume of AI training data sets at lowest cost.
Apart from training data for agriculture,it is offering the set of data for other fields like automotive, retail, drones, autonomous vehicles, security cameras and computer vision based other AI models. The training data for AI here is developed in the highly secured environment to ensure the privacy & safety.
Image Annotation for Live Stock Management
Animal husbandry is now easier and productive with AI-enabled machines. Yes, animals can be monitored through drones or AI-enabled machines keeping them in count and inside the campus. Again image annotation is the technique, used to make such animals recognizable in various scenarios. Bounding box and semantic image segmentation helps to make the animals recognizable with accuracy.