How to Perform Quality Check on Agriculture Satellite Imagery Dataset

Satellite images from a vast distance can capture a wide-angle viewing zone, making artificial intelligence more effective in a range of fields. Furthermore, AI systems that employ satellite images may learn to foresee different circumstances after analyzing the situation with satellite imaging datasets created particularly for AI models.Furthermore, a considerable quantity of training data is required to build such models using machine learning or deep learning approaches. Different sorts of aerial views of various objects, such as agricultural fields, forests, cities for urban planning and management, and numerous other manmade structures, are included in this satellite image data.Significance of high-quality Satellite Image DatasetIt doesn't matter how brilliant a model architecture is if it isn't trained with adequate data. On the other hand, if given a suitable dataset for training, even the most basic model architecture may be sufficient to complete the task.And, while there has been a lot published on machine learning model building, we believe that dataset preparation has been overlooked, which is fair given that it isn't a particularly exciting subject and takes a long time to do right. Unfortunately, grasping the need to 'build a decent dataset' was a long and unpleasant process.So, what constitutes a "good" ...


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