The objectives of this study were 1) to determine, whether or not the proposed feature vector-based convolutional neural network (V-CNN) is the most suitable and best model of colony quality recognition from the morphological and textural features of a segmented colony; 2) to confirm the promising results of colony quality recognition through use of an accurate cross-validation process; 3) to demonstrate the superiority of the proposed deep V-CNN learning approach over the SVM classification system.