Keywords : Neural Network

Identification of CT Lung Tumor Using Fuzzy Clustering Algorithm

Jalal deen K; Karthigai Priya G; Magesh B; Kubendran R

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICEST 1S, Pages 30-33
DOI: 10.47392/irjash.2021.016

The main principle for the system-based study of lung cancers in CT images is cancer cell recognition and segmentation. Anyhow, in low-contrast pictures, it is a complex job as the low-level images are too small to detect. We are proposing a new technique in this project for the automated detection of lung cancers. Alternatively, by probability density function estimation, we enhance the intensity contrast of CT images. We use the expectation maximization / maximization of the posterior marginal to find cancerous areas. Finally, to decrease noise and classify focal cancers, we use shape limitation. The resolution of more than 95 percent of this fuzzy-based segmentation method is achieved and 9 percent accuracy is also given.

Intelligence slicing: A synthesized framework to integrate artificial intelligence into 5G networks

Chandrakala V; Surya Kumar M S R

International Research Journal on Advanced Science Hub, 2020, Volume 2, Issue 8, Pages 57-61
DOI: 10.47392/irjash.2020.94

For best-performing networks from 5G and above, it must support a wide range of needs. It is understood that more transmission, resource assistance and communication systems will be required. Achieving these tasks can be challenging as network infrastructure becomes more complex and massive. A good solution is to incorporate more robust AI technology that has been tested to provide answers ranging from channel prediction to autonomous network management, as well as network security. Today, however, the latest technology to integrate AI into wireless networks is limited to using a unique AI algorithm to solve a specific problem. A comprehensive framework that can fully utilize the power of AI in solving various network problems remains an open problem. Therefore, this paper introduces the idea of the spy pieces on which the AI unit is installed and delivers on one condition. Intelligence units are used to flexibly control the intelligence of AI algorithms with two comprehension strategies to perform different intellectual tasks: 1) Neural network-based channel predictions and 2) Industrial network-based security acquisition, to illustrate this framework.