Abstract: The paddy agronomy in the Asia-pacific region has gained a prominent role in connection with the major rice production area in over the decades. The research aims to investigate the aerial ...

Abstract: The radio communication division of the International Telecommunication Union (ITU-R) has recently adopted integrated sensing and communication (ISAC) among the key usage scenarios for ...

Abstract: The booming development of deep learning applications and services heavily relies on large deep learning models and massive data in the cloud. However, cloud-based deep learning encounters ...

Abstract: Object detection plays a key role in helping to enable industrial quality control and safety monitoring. This article introduces a lightweight and efficient transformer-based object ...

Abstract: Developing new diagnostic models based on the underlying biological mechanisms rather than subjective symptoms for psychiatric disorders is an emerging consensus. Recently, machine learning ...

Abstract: In the context of rapid advancements in artificial intelligence (AI), enhancing AI literacy among college students is crucial for promoting the sustainable development of higher education.

Abstract: The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the ...

Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...

Abstract: Space-Air-Ground Integrated Networks (SAGIN) is considered as the key structure of the next generation network. The space satellites and air nodes are potential candidates to assist and ...

Abstract: The rapid growth of intelligent sensing capabilities and super computation power in 6G mobile communication systems has facilitated their application in diverse domains such as smart health, ...

Abstract: Short-term precipitation forecasting remains challenging due to the difficulty in capturing long-term spatiotemporal dependencies. Current deep learning methods fall short in establishing ...

Abstract: Generative Adversarial Networks are a class of artificial intelligence algorithms that consist of a generator and a discriminator trained simultaneously through adversarial training. GANs ...