Open AccessRETRACTED: An enhanced approach for object detection using wavelet based neural network
Author(s) -
G. Krishnaveni,
B. Lalitha Bhavani,
N V S K Vijaya Lakshmi
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1228/1/012032
Subject(s) - computer science , artificial intelligence , object (grammar) , sort , process (computing) , field (mathematics) , artificial neural network , pattern recognition (psychology) , machine learning , information retrieval , mathematics , pure mathematics , operating system
Object recognition indicates colossal increment in the field of picture investigation. The required arrangement of picture objects are recognized and recovered based on object recognition. The procedure associated with Object recognition incorporates division, arrangement, and gathering of articles that can be connected in different designing and logical teaches, for example, science, drug, advertising, brain science, man-made consciousness, PC vision, and remote detecting. A large portion of the ongoing plans in picture investigation confront certain bad marks particularly in protest acknowledgment exactness. Indeed, even in Object recognition, the off base order concerns flawed protest extraction. One of the fundamental detriments in existing methods to picture grouping is that immense measure of information needs in learning plans which is a tedious procedure because of the human time and endeavors. In this way, a novel proposition is expected to successfully separate the state of the protest with appropriate characterization procedure. The topological course of action of the WNN contains the concealed neutrons in the wavelet layer with various goals. Wavelet Neural Network idea is utilized for picture handling which is by all accounts exceptionally productive. WNN structure offers the parallel handling of pictures and preparing process makes the system appropriate for the different sort of picture handling. In this work, a novel characterization system called Affluence based Image Classification (AIC) is proposed utilizing a wavelet neural system.