Abstract: A method for image classification includes accessing a plurality of images of at least a portion of a gastrointestinal tract (GIT) captured by a capsule endoscopy device and for each image of the plurality of images: providing a classification score for each segment of a plurality of consecutive segments of the GIT by a deep learning neural network, and providing a classification probability for each segment of the plurality of consecutive segments of the GIT based on the classification scores by a classical machine learning classifier. The method further includes determining a classification for each image to one segment of the plurality of consecutive segments of the GIT based on processing a signal corresponding to the classification probabilities of the plurality of images.