Automatic classification is a method that classifies images based on a model trained from an initial set of manual labels. The advantage of automatic classification over manual labeling is that manual labeling is time-consuming and expensive, so it’s very effective to let computer do the job which can be automated with efficient algorithms. On the other hand, manual classification have some advantages over automated system: manual classification provides extra information for further analysis by “ground truthing” data processing accuracy. For example, you could show some samples where manual labelling are different then automatic one or tell user what area of samples are not classified correctly. Also manual process gives opportunity to use existing knowledge about certain objects/phenomena which help in modeling of target object better .
Automatic Classification vs manual classification Automatic classification is a method that classifies images based on a model trained from an initial set of manual labelling. The advantage of automatic classification over manual labelling is that manual labelling is time-consuming and expensive, so it’s very effective to let computer do the job which can be automated with efficient algorithms. On the other hand, manual classification have some advantages over automated system: manual classification provides extra information for further analysis by “ground truthing” data processing accuracy. For example, you could show some samples where manual labelling are different then automatic one or tell user what area of samples are not classified correctly. Also manual process gives opportunity to use existing knowledge about certain objects/phenomena which help in modelling of target object better .
Manual Classification vs manual annotation manual classification is a technique that classifies images based on manual labelling. The advantage of manual classification over automatic system is that manual process gives opportunity to use existing knowledge about certain objects/phenomena which help in modelling of target object better. On the other hand, manual annotations are time-consuming and expensive, so it’s not effective to let human do the job which can be automated with efficient algorithms. In many cases manual annotation require special skills and long training, moreover there isn’t any guarantee that person annotating data will mark exactly same points as another expert annotator will do. So manual annotation returns more accurate results then manual subset but less accurate then automatic classification.
What is point cloud?
A point cloud is a set of data points in some coordinate system (x,y,z). The term typically refers to raster or vector data collected from an optical scanner or LIDAR with a laser beam as a light source. In reality it’s all just three dimensional dataset containing samples inside each unit cell with coordinates for each sample, encoded as Red Green Blue color intensity values at each location.
