{'fraction_non_alphanumeric': 0.013916500994035786, 'fraction_numerical': 0.0, 'mean_word_length': 5.333333333333333, '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}}
Fruits, Vegetable and Plants Category Recognition Systems Using Convolutional Neural Networks : A Review

This paper reviews the systems and methods that have been employed in the recognition of the fruits, vegetables and other plant parts or the entire plant itself .Deep learning algorithms are the current trend in computer vision applications and are broadly employed in agricultural domains for identification of plants and its parts, soil type classification, water resources, harvesting prediction and in fertilizer and pest management. The deep learning algorithm CNN and its types are used widely in current research fields. Higher accuracies are obtained for the detection of plants parts such as leaves and fruits. This can be applied in the field of robotics, agriculture and in some medicinal industries where identification of plants, its parts and where weed detection is necessary. Plant identification is of great value to the agriculturists and medical industries which wants to automate.