How to Get Machine Learning Training Datasets for Agriculture?

To get the training data for machine learning in agriculture first of all you need to decide what type of AI model you are working or which type of agriculture related datasets you need for your project. Actually, there could be multiple types of machine learning based models that can be developed for agriculture and farming sector to improve the productivity and crop yield.

Agriculture Datasets for Machine Learning and AI

Basically most of the machine learning models for agriculture are developed in the form of robots, drones or other automated machines that can monitor the crops through computer vision technology. And to train the computer vision based visual perception models, you need training data sets that can help to detect or recognize the objects in the images to these machines.

Get Annotated Images of Crops, Fruits, Plants & Agricultural Fields   

And making the object of interest in the mages like crops, fruits, vegetables, plants (wanted or unwanted) and agricultural fields recognizable for machines, it should be properly annotated with right technique. And there are multiple types of image annotation technique used to annotate the images precisely making the different crops or plants recognizable with extra precision. 

Training Datasets for Harvesting & Monitoring in Agricultural

Actually, there are two types of training datasets needed for machine leaning in agriculture. AI training data for robots that can detect crops or plants and do automated harvesting. Similarly, drones are used for Ariel view of matured crops for monitoring, and soil condition monitoring. Images annotated with bounding box annotation is used to create the training datasets for machine learning.

Agriculture Training Data for Field Mapping & Geosensing 

Agricultural fields need to be monitored to check whether it ready to sowing or not and check the soil condition or moister level to decide right time for seeding or plantation. Similarly, machine learning data also included 3D mapping of agricultural filed using the drones to check maturity level of crops and determine the harvesting time with precision for higher productivity and crop yield.      

How to Get Training Data for Machine Learning in Agriculture?

To get the right training datasets for agriculture you need huge amount for annotated data sets. And data annotation or image annotation is the best process that can create such data sets for machine learning models developed for agriculture and farming. Anolytics is the right company, providing the best quality training data sets for machine learning and deep learning in agriculture.  

Also Read : How to Improve Computer Vision in AI for Precision Agriculture

It can provide the annotated images of all types of crops, fruits, vegetable and other plants produced in agricultural sector. It is expert in all types of image annotation techniques like bounding box, semantic segmentation, polygon annotation, 3D Cuboid Annotation and Polyline annotation to make different types of objects recognizable for machine learning in Agriculture and various other fields.