{'fraction_non_alphanumeric': 0.01403061224489796, 'fraction_numerical': 0.0, 'mean_word_length': 4.607142857142857, '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}}
Detection of Wild Oats based on Support Vector Machine Algorithms

Wild Oat degrades the quality and yield of wheat plants. Machine learning technique is used to detect wheat wild oat disease. Digital camera records the image of a wheat differentiated between healthy wheat and wild oats. The captured image is processed to determine whether each test picture is diseased or not. The comparison result illustrates a diseased and uninfected plant taken from the test data. Our target is to differentiate between wild oats and wheat. Our motivation to do this project is that to our knowledge, no one tried to solve this problem until now; a lot of papers, experiments, and reports had been made to compare Wheat and any other crop not solving the existence of Wild Oats with the Wheat.