Robotics & Machine Learning Daily News2024,Issue(Oct.2) :81-82.

Study Findings on Artificial Intelligence Described by Researchers at College of Information Science and Engineering (Graphic association learning: Multimodal f eature extraction and fusion of image and text using artificial intelligence ... )

Robotics & Machine Learning Daily News2024,Issue(Oct.2) :81-82.

Study Findings on Artificial Intelligence Described by Researchers at College of Information Science and Engineering (Graphic association learning: Multimodal f eature extraction and fusion of image and text using artificial intelligence ... )

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting out of Guangxi, Pe ople’s Republic of China, by NewsRx editors, research stated, “With the advancem ent of technology in recent years, the application of artificial intelligence in real life has become more extensive. Graphic recognition is a hot spot in the c urrent research of related technologies.” The news correspondents obtained a quote from the research from College of Infor mation Science and Engineering: “It involves machines extracting key information from pictures and combining it with natural language processing for in-depth un derstanding. Existing methods still have obvious deficiencies in fine-grained re cognition and deep understanding of contextual context. Addressing these issues to achieve high-quality image-text recognition is crucial for various applicatio n scenarios, such as accessibility technologies, content creation, and virtual a ssistants. To tackle this challenge, a novel approach is proposed that combines the Mask R-CNN, DCGAN, and ALBERT models. Specifically, the Mask R-CNN specializ es in high-precision image recognition and segmentation, the DCGAN captures and generates nuanced features from images, and the ALBERT model is responsible for deep natural language processing and semantic understanding of this visual infor mation. Experimental results clearly validate the superiority of this method.”

Key words

College of Information Science and Engin eering/Guangxi/People’s Republic of China/Asia/Artificial Intelligence/Emer ging Technologies/Machine Learning/Natural Language Processing/Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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