{'fraction_non_alphanumeric': 0.011583011583011582, 'fraction_numerical': 0.0, 'mean_word_length': 5.92, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Learning Face Recognition Classifiers by Incorporating Human Perceptions

We propose a novel approach that employs human perception to improve the learning for face-recognition. By considering that the training examples are finite samples on the face manifold, we introduce the concept of appearance morphing curve that contains significant information for identifying facial images of different persons. By employing this concept, an effective method is introduced to increase automatic face recognition performances.