Multimodality neuromonitoring (MNM) refers to the integration, display, and interpretation of more than one physiological measurement source to guide clinical treatment for patients with brain injuries (Box 1). Monitoring cardiac function using electrocardiography (ECG), blood pressure, and volume plethysmography (Spo2) is a standard method in intensive care settings to identify and treat significant changes in … Read more
Click the “Chinese Journal of Practical Pediatrics” above to follow us Special Discussion│Clinical Applications of Multimodal MRI in Neonatal Encephalopathy Hou Ana, Fu Jianhua Chinese Journal of Practical Pediatrics 2023 Vol.38(5): 344-349 Abstract Neonatal encephalopathy has various types, such as hypoxic-ischemic encephalopathy, bilirubin encephalopathy, hypoglycemic encephalopathy, encephalopathy of prematurity, sepsis-associated encephalopathy, genetic metabolic encephalopathy, and … Read more
1 What Is Multimodal Discourse 1.1 What is Discourse? Discourse is an important means for humans to convey information, serving as a linguistic unit with communicative significance or contextual semantics. 1.2 The forms of discourse can be monomodal (单模态) or multimodal (多模态). Here, mode refers to the pattern or method of information transmission in discourse. … Read more
“Complementarity” and “Integration” Multimodal imaging unveils the mysteries of life from all angles 1 Understanding Life: Multimodal Biomedical Imaging Technology In recent years, rapidly developing biomedical imaging technologies can depict the structure and function of living organisms at different scales, such as in vivo, tissue, and molecular levels. However, single-modal representation is easily affected by … Read more
Paper Information Title: A General Spatial-Frequency Learning Framework for Multimodal Image Fusion A General Spatial-Frequency Learning Framework for Multimodal Image Fusion Authors: Man Zhou; Jie Huang; Keyu Yan; Danfeng Hong; Xiuping Jia; Jocelyn Chanussot; Chongyi Li Source Code Link: https://github.com/manman1995/Awaresome-pansharpening Innovations of the Paper 1 Spatial-Frequency Information Integration Network (SFINet): The first proposal to simultaneously … Read more
Source: AI Technology Online Just yesterday, OpenAI officially released the GPT-4o model, which supports real-time reasoning in audio, visual, and text multimodal scenarios. Besides eagerly wanting to use the GPT-4o model, everyone must also want to understand some of the implementation details of this model. Before GPT-4o, you could interact with ChatGPT in voice mode, … Read more
Source: Graph Science Lab This article is about 4000 words long and is recommended to be read in 8 minutes. This article introduces the transition states in multimodal learning—Latent Modal. Background With the advancement of large models, single-modal large models can no longer adequately meet the needs of real-world work. Many research teams and institutions … Read more
MLNLP ( Machine Learning Algorithms and Natural Language Processing ) community is a well-known natural language processing community both domestically and internationally, covering NLP master’s and Ph.D. students, university professors, and researchers in enterprises. The vision of the community is to promote communication between the academic and industrial communities of natural language processing and machine … Read more
Introduction to University Student Innovation Training Project Subtitle Translation Strategies from a Multimodal Perspective Project Members | Ma Yuqi, Di Bao Supervisor | Chang Chengguang 1 1 1 What is Multimodality? First, what do we mean by modality? Every source or form of information can be referred to as a modality. For example, humans have … 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