Kaushlendra Yadav^*, Anuj Singh, Arvind Kumar Tiwari

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3767-3782, 2023, DOI:10.32604/csse.2023.033991

Abstract Forecasting the weather is a challenging task for human beings because of the unpredictable nature of the climate. However, effective forecasting is vital for the general growth of a country due to the significance of weather forecasting in science and technology. The primary motivation behind this work is to achieve a higher level of forecasting accuracy to avoid any damage. Currently, most weather forecasting work is based on initially observed numerical weather data that cannot fully cover the changing essence of the atmosphere. In this work, sensors are used to collect real-time data for a particular location to capture the… More >

Romany F. Mansour^1,*, Maha M. Althobaiti²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3945-3959, 2022, DOI:10.32604/cmc.2022.026515

Abstract Recently, the Internet of Medical Things (IoMT) has become a research hotspot due to its various applicability in medical field. However, the data analysis and management in IoMT remain challenging owing to the existence of a massive number of devices linked to the server environment, generating a massive quantity of healthcare data. In such cases, cognitive computing can be employed that uses many intelligent technologies–machine learning (ML), deep learning (DL), artificial intelligence (AI), natural language processing (NLP) and others–to comprehend data expansively. Furthermore, breast cancer (BC) has been found to be a major cause of mortality among ladies globally. Earlier… More >

Yujie Zhou¹, Jin Liu^1,*, Yurong Xie¹, Y. Ken Wang²

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 715-733, 2021, DOI:10.32604/iasc.2021.020184

Abstract Text recognition is a crucial and challenging task, which aims at translating a cropped text instance image into a target string sequence. Recently, Convolutional neural networks (CNN) have been widely used in text recognition tasks as it can effectively capture semantic and structural information in text. However, most existing methods are usually based on contextual clues. If only recognize a single character, the accuracy of these approaches can be reduced. For example, it is difficult to distinguish 0 and O in the traditional CNN network because they are very similar in composition and structure. To solve this problem, we propose… More >