Harsh Mankodiya¹, Priyal Palkhiwala¹, Rajesh Gupta^1,*, Nilesh Kumar Jadav¹, Sudeep Tanwar¹, Osama Alfarraj², Amr Tolba², Maria Simona Raboaca^3,4,*, Verdes Marina⁵

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1123-1142, 2023, DOI:10.32604/cmc.2023.038556

Abstract The amalgamation of artificial intelligence (AI) with various areas has been in the picture for the past few years. AI has enhanced the functioning of several services, such as accomplishing better budgets, automating multiple tasks, and data-driven decision-making. Conducting hassle-free polling has been one of them. However, at the onset of the coronavirus in 2020, almost all worldly affairs occurred online, and many sectors switched to digital mode. This allows attackers to find security loopholes in digital systems and exploit them for their lucrative business. This paper proposes a three-layered deep learning (DL)-based authentication framework to develop a secure online… More >

Xi Zhao¹, Haizheng Yu^1,*, Hong Bian²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 181-198, 2023, DOI:10.32604/cmc.2023.041479

Abstract In recent years, Pix2Pix, a model within the domain of GANs, has found widespread application in the field of image-to-image translation. However, traditional Pix2Pix models suffer from significant drawbacks in image generation, such as the loss of important information features during the encoding and decoding processes, as well as a lack of constraints during the training process. To address these issues and improve the quality of Pix2Pix-generated images, this paper introduces two key enhancements. Firstly, to reduce information loss during encoding and decoding, we utilize the U-Net++ network as the generator for the Pix2Pix model, incorporating denser skip-connection to minimize… More >

Xukun Zhang¹, Wei Song^1,2,3,*, Ganghua Lin^2,4, Yuxi Shi⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6181-6193, 2022, DOI:10.32604/cmc.2022.027215

Abstract In ground-based observations of the Sun, solar images are often affected by appearance of thin clouds, which contaminate the images and affect the scientific results from data analysis. In this paper, the improved Pixel to Pixel Network (Pix2Pix) network is used to convert polluted images to clear images to remove the cloud shadow in the solar images. By adding attention module to the model, the hidden layer of Pix2Pix model can infer the attention map of the input feature vector according to the input feature vector. And then, the attention map is multiplied by the input feature map to give… More >

Wei Song^1,2,3, Haolin Wang¹, Xinping Zhang¹, Jianxin Xia^4,*, Tongmu Liu⁵, Yuxi Shi⁶

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1449-1462, 2022, DOI:10.32604/cmc.2022.027213

Abstract Deep-sea mineral image segmentation plays an important role in deep-sea mining and underwater mineral resource monitoring and evaluation. The application of artificial intelligence technology to deep-sea mining projects can effectively improve the quality and efficiency of mining. The existing deep learning-based underwater image segmentation algorithms have problems such as the accuracy rate is not high enough and the running time is slightly longer. In order to improve the segmentation performance of underwater mineral images, this paper uses the Pix2PixHD (Pixel to Pixel High Definition) algorithm based on Conditional Generative Adversarial Network (CGAN) to segment deep-sea mineral images. The model uses… More >

Xian Wu¹, Wei Song^1,2,3,*, Xukun Zhang¹, Ganghua Lin^2,4, Haimin Wang^5,6,7, Yuanyong Deng^2,4

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3497-3512, 2022, DOI:10.32604/cmc.2022.022325

Abstract Sky clouds affect solar observations significantly. Their shadows obscure the details of solar features in observed images. Cloud-covered solar images are difficult to be used for further research without pre-processing. In this paper, the solar image cloud removing problem is converted to an image-to-image translation problem, with a used algorithm of the Pixel to Pixel Network (Pix2Pix), which generates a cloudless solar image without relying on the physical scattering model. Pix2Pix is consists of a generator and a discriminator. The generator is a well-designed U-Net. The discriminator uses PatchGAN structure to improve the details of the generated solar image, which… More >