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Article | 01-March-2015

A NOVEL APPROACH OF COMBINING STEGANOGRAPHY ALGORITHMS

Hamdan Lateef Jaheel, Zou Beiji

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 90–106

Article | 03-December-2014

SECURITY METHOD FOR COMBINATION STEGANOGRAPHY ALGORITHMS ON TRANSFORM DOMAIN FOR JPEG IMAGES

Hamdan L. Jaheel, Zou Beiji

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 4, 1962–1979

research-article | 30-November-2020

Performance evaluation of brain tumor detection using watershed Segmentation and thresholding

the image. The image obtained is then used for watershed segmentation. K-means clustering is executed after watershed segmentation, followed by MSER detection. The detected tumor region is obtained and highlighted in the final output. Finally, a performance evaluation of the proposed method is carried out based on several parameters such as Structural Similarity Index Measure (SSIM), Feature Similarity Index Measure (FSIM) and Peak Signal-to-Noise Ratio (PSNR). The values obtained provide an

Shruti Mishra, Noyonika Roy, Meghana Bapat, Abhishek Gudipalli

International Journal on Smart Sensing and Intelligent Systems, Volume 14 , ISSUE 1, 1–12

Article | 11-January-2021

Conditional GAN-based Remote Sensing Target Image Generation Method

background under small samples. And carried out the relevant experimental verification, at the same time, the objective and quantitative evaluation of this algorithm based on the conditional background image generation. It briefly introduces the relevant basic theory of the evaluation method. The image generation algorithms of different generator structures are compared through experiments. Under the same conditions of the background image, the peak signal-to-noise ratio (PSNR) of the image generation

Haoyang Liu, Zhiyi Hu, Jun Yu, Shouyi Gao

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 4, 66–74

Article | 30-November-2020

Motion Blur Image Restoration by Multi-Scale Residual Neural Network

Xu Hexin, Zhao Li, Jiao Yan

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 1, 57–67

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