Adversarial Training

Multimodal Cognitive Computing: Theoretical Insights and Future Directions

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Multimodal Cognitive Computing: Theoretical Insights and Future Directions

In daily life, humans utilize various senses such as vision and hearing to understand the surrounding environment. By integrating multiple perceptual modalities, a holistic understanding of events is formed. To enable machines to better mimic human cognitive abilities, multimodal cognitive computing simulates human “synaesthesia”, exploring efficient perception and comprehensive understanding methods for multimodal inputs such … Read more

Deep Learning Advancements in Multimodal AI Models

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Deep Learning Advancements in Multimodal AI Models

It has been a whole year since the emergence of ChatGPT, GPT-4, and other innovations that sparked a new wave of transformation in artificial intelligence. During this year, numerous companies both domestically and internationally have entered the “arena” of large models, accelerating the iteration and leap of large model technologies. The unprecedented capability of large … Read more

Multimodal Biomedical AI in the Era of Large Models

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Multimodal Biomedical AI in the Era of Large Models

Most applications of artificial intelligence in medicine utilize a single data modality to address tasks within a narrow scope, such as computed tomography (CT) scans or retinal photographs. However, clinicians integrate multi-source, multimodal data for diagnosis, prognosis assessment, and treatment planning. In this review, the authors explore the applications of multimodal datasets in healthcare, the … Read more

Multimodal Visual Structure Learning

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Multimodal Visual Structure Learning

Author / Li Xi 0 Introduction This article organizes previous research on multimodal visual structure learning from a new perspective, focusing on the characteristics and applications of spherical panoramic images. Spherical images are mostly related to fisheye or 360° panoramic views, containing a wealth of structural knowledge, primarily aimed at applications such as autonomous driving, … Read more

How to Handle Missing Modalities? A Comprehensive Review of Deep Multimodal Learning with Missing Modalities

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How to Handle Missing Modalities? A Comprehensive Review of Deep Multimodal Learning with Missing Modalities

MLNLP community is a renowned machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university professors, and corporate researchers. The Vision of the Community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners. Reprinted from | … Read more

Multimodal AI Models Aid Clinical Decision-Making in Medicine

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Multimodal AI Models Aid Clinical Decision-Making in Medicine

On August 26, 2024, Professor Shen Lin’s team from Peking University Cancer Hospital and Professor Dong Bin’s team from Peking University published a groundbreaking research article titled “Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data” in the journal Signal Transduction and Targeted Therapy (Impact Factor: 40.8). This study … Read more

Research Progress on Multimodal Large Language Models

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Research Progress on Multimodal Large Language Models

About 3800 words, recommended reading time is 7 minutes. This article provides a comprehensive overview of MM-LLMs. 1. Introduction Multimodal large language models (MM-LLMs) have made significant progress over the past year by optimizing modality alignment and human intent alignment, enhancing existing unimodal foundational models (LLMs) to support various MM tasks. This article provides a … Read more

How Multimodal Large Models Reshape Computer Vision

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How Multimodal Large Models Reshape Computer Vision

Introduction: The author will delve into the concept of Multimodal Large Language Models (MLLMs). This model not only inherits the powerful reasoning capabilities of Large Language Models (LLMs) but also integrates the ability to process multimodal information, enabling it to easily handle various types of data, such as text and images.©️【Deep Blue AI】 In short, … Read more

What Is Multimodal Learning?

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What Is Multimodal Learning?

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

Multimodal AI: New Directions and Challenges in Intelligent Development

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Multimodal AI: New Directions and Challenges in Intelligent Development

Multimodal AI The Future of Artificial Intelligence New Directions and Challenges in Intelligent Development In the rapidly advancing tide of technology, artificial intelligence is evolving at an astonishing speed, and the rise of multimodal AI has brought us an unprecedented intelligent revolution. From the previous single modality to today’s diverse integration, multimodal AI is reshaping … Read more