Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Is Internet becoming a Major Contributor for Global warming - The Online Carbon Footprint
Volume-2 | Issue-4
Augmented Reality in Education
Volume-2 | Issue-4
A Study on Various Task-Work Allocation Algorithms in Swarm Robotics
Volume-2 | Issue-2
IoT based Biotelemetry for Smart Health Care Monitoring System
Volume-2 | Issue-3
Tungsten DiSulphide FBG Sensor for Temperature Monitoring in Float Glass Manufacturing
Volume-2 | Issue-4
GUI based Industrial Monitoring and Control System
Volume-3 | Issue-2
AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1
Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1
Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3
Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3
Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2
Volume - 3 | Issue - 2 | june 2021
Published
04 July, 2021
In recent years, digital watermarking has improved the accuracy and resistance of watermarked images against many assaults, such as various noises and random dosage characteristics. Because, based on the most recent assault, all existing watermarking research techniques have an acceptable level of resistance. The deep learning approach is one of the most remarkable methods for guaranteeing maximal resistance in the watermarking system's digital image processing. In the digital watermarking technique, a smaller amount of calculation time with high robustness has recently become a difficult challenge. In this research study, the light weight convolution neural network (LW-CNN) technique is introduced and implemented for the digital watermarking scheme, which has more resilience than any other standard approaches. Because of the LW-CNN framework's feature selection, the calculation time has been reduced. Furthermore, we have demonstrated the robustness of two distinct assaults, collusion and geometric type. This research work has reduced the calculation time and made the system more resistant to current assaults.
Keywordsdigital water marking convolution neural network
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