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Recent studies have shown that computed tomography (CT) scan images can characterize COVID-19 disease in patients. Several deep learning (DL) methods have been proposed for diagnosis in the literature, including convolutional neural networks (CNN). But, with inefficient patient classification models, the number of ‘False Negatives’ can put lives at risk. The primary objective is to improve the model so that it does not reveal ‘Covid’ as ‘Non-Covid’. This study uses Dense-CNN to categorize patients efficiently. A novel loss function based on cross-entropy has also been used to impro...

About the racial healing worked at the color foundation had been done, and i will be totally say, slightly skeptical, when i hear the word. i have materialist conception of how the stuff works. it's about who owns property, how the loss function, but the work they have done is fascinating. they do this interesting work with groups, and it is a way in to get from what i, would say, is the psychological, to the political. i think there is an interesting story to tell about how it works. it's particularly important in early 2023, which you see several ways of consciousness about racism, racial hi...

Generative Adversarial Network (GAN), deemed as a powerful deep-learning-based silver bullet for intelligent data generation, has been widely used in multi-disciplines. Furthermore, conditional GAN (CGAN) introduces artificial control information on the basis of GAN, which is more practical for many specific fields, though it is mostly used in domain transfer. Researchers have proposed numerous methods to tackle diverse tasks by employing CGAN. It is now a timely and also critical point to review these achievements. We first give a brief introduction to the principle of CGAN, then focus on how...

Rashtriya Swayamsevak Sangh chief Dr Mohan Bhagwat said,