Grey wolf optimization (GWO) with the convolution neural network (CNN)-based pattern recognition system

ABSTRACT

The dynamic video frame dataset’s automated feature analysis addresses the complexity of intensity mapping with normal and abnormal classes. Iterative modelling is needed to learn the component of a video frame in several patterns for various video frame data types for threshold-based data clustering and feature analysis. GWO optimises the Convoluted Pattern of Wavelet Transform (CPWT) feature vectors employed in this paper's CNN feature analysis technique. A median filter reduces noise and smooths the video frame before normalising it. Edge information represents the video frame's bright spot boundary. Neural network based video frame classification clusters pixels using feature recurrent learning with minimal dataset training. The filtered video frame's features were evaluated using complex wavelet transformation feature extraction algorithms. These features demonstrate video frame spatial and textural classifications. CNN classifiers help analyse video frame instances and classify action labels. Categorization improves with the fewest training datasets. This strategy may be beneficial if compared to optimal practises.

KEYWORDS:

• Action recognition
• pattern recognition system
• convoluted pattern of wavelet transform (CPWT)
• grey wolf optimization (GWO)
• convolution neural network (CNN)
• Deep bidirectional long short-term memory (DBiLSTM)
• Deep Convolution Symmetric Neural Network with PCANET Weaklysupervisedaction localization (WSAL)
• UCF sports dataset

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Aatif Jamshed

Aatif Jamshed is working as Assistant Professor (Senior Scale) at the ABES Engineering College, Ghaziabad (U.P). He is Pursuing a PhD from Veer Madho Singh Bhandari, Uttarakhand Technical University Dehradun; A State Govt. University He is a member of IEEE, UACEE, IAENG, IACSIT, CSTA etc. He has 13 years of experience in academics. He has a specialization in progressive databases. He is the reviewer of many International Journals. He has experience in real–life projects from a leading IT company in India with proficiency in Python.

Bhawna Mallick

Dr. Bhawna Mallick is working as Dean of Academics in MIET Meerut and has served as Professor and Head of the Department at Galgotia College of Engineering and Technology. She has also served as a senior consultant at Maverick Quality Advisory Services Pvt. Ltd Ghaziabad, India, she is having 23+ years of experience. Degree(s) PhD, M. Tech and B.E (Computer Technology). She has published more than 30 Research papers in reputed International Refereed Journals/ Conferences. She has organized 2 International Conferences and many workshops & Seminars.

Rajendra Kumar Bharti

Dr. Rajendra Kumar Bharti is working as Associate Professor at Bipin Tripathi Kumaon Institute of Technology, Dwarahat, Uttarakhand University. He is a member of many reputed societies. He has a specialization in Data Compression and Network Security. He is the reviewer of many International Journals. He has an experience in real–life projects.