1 Introduction to the Algorithm The Knowledge Graph is an important branch of artificial intelligence technology, proposed by Google in 2012. It is a structured semantic knowledge base used to describe concepts in the physical world and their interrelationships in symbolic form. Its basic unit consists of “entity-relation-entity” triples, as well as entity and its … Read more
This is the 907th article shared by ITC of Wenzhou Medical University Smart Teaching Tools Introduction to Knowledge Graphs Diverse Data Fusion Structured Representation Dynamic Development Preface Knowledge Graph, as an important branch in the field of artificial intelligence, provides strong support for solving the problem of how to effectively organize, store, and retrieve information … Read more
Exciting Recommendations By Wang Shasha, R&D Center, Agricultural Bank of China Emotion computing aims to construct an intelligent system that can perceive, recognize, and understand human emotions, achieving intelligent, sensitive, and natural responses to human feelings. Early on, the industry commonly employed unimodal emotion computing technologies, such as micro-expression recognition, speech emotion recognition, and text … Read more
Click the above“Mechanical and Electronic Engineering Technology” to follow us 1. Definition and Concept Multimodal learning is a machine learning method that utilizes various data modalities to train models, which may include text, images, audio, video, etc. Multimodal AI technology integrates multiple data patterns, such as text, images, videos, and audio, to provide a more … Read more
Source: Data Analysis and Applications 1 Introduction Our experience of the world is multimodal — we see objects, hear sounds, feel textures, smell odors, and taste flavors. A modality refers to the way something occurs or is experienced; when a research question involves multiple modalities, it has multimodal characteristics. For artificial intelligence to make progress … Read more
Multimodal fusion aims to integrate information from various modalities to achieve more accurate predictions. Significant progress has been made in multimodal fusion across a wide range of scenarios including autonomous driving and medical diagnosis. However, the reliability of multimodal fusion in low-quality data environments remains largely unexplored. This paper reviews the common challenges and recent … Read more