多模态深度学习（Multimodal Deep Learning）是人工智能领域的一个分支，专注于开发能够处理多种数据类型的模型。这些数据类型，即模态，包括文本、图像、音频、视频以及传感器数据等。多模态深度学习旨在构建更强大、多功能的AI系统，这些系统能够理解并处理复杂的现实世界数据，从而实现人工通用智能（AGI）的方...
介绍: NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.NeuralTalk是一个Python的从图像生成自然语言描述的工具。它实现了Google (Vinyals等,卷积神经网络CNN + 长短期记忆LSTM) 和斯坦福 (Karpathy and Fei-Fei, CNN + 递归神经网络RNN...
Deep Learning in Neural Networks- This technical report provides an overview of deep learning and related techniques with a special focus on developments in recent years. 主要看点是深度学习近两年(2012-2014)的进展情况。 Tutorials UFLDL Tutorial 120 Deep Learning Tutorial from Stanford:斯坦福的官方Tutori...
多模态深度学习(英文名:Multimodal Deep Learning)是人工智能(AI)的一个子领域,其重点是开发能够同时处理和学习多种类型数据的模型。这些数据类型,或称模态,可以包括文本、图像、音频、视频和传感器数据等。通过结合这些不同的模式,多模态深度学习旨在创建更强大和多功能的人工智能系统,能够更好地理解、解释复杂的现实...
介绍: NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.NeuralTalk是一个Python的从图像生成自然语言描述的工具。它实现了Google (Vinyals等,卷积神经网络CNN + 长短期记忆LSTM) 和斯坦福 (Karpathy and Fei-Fei, CNN + 递归神经网络RNN...
learningfor singlemodalities(e.g.,text,imagesoraudio).Inthiswork,weproposeanovelap- plicationofdeepnetworkstolearnfeaturesovermultiplemodalities.Wepresenta seriesoftasksformultimodallearningandshowhowtotrainadeepnetworkthat learnsfeaturestoaddressthesetasks.Inparticular,wedemonstratecrossmodal- ityfeaturelearning,...
A Survey on Deep Learning for Multimodal Data Fusion With the wide deployments of heterogeneous networks, huge amounts of data with characteristics of high volume, high variety, high velocity, and high veracity are generated. These data, referred to multimodal big data, contain abundant in... J...
《Multimodal Deep Learning》 介绍:来自斯坦福大学的Multimodal Deep Learning papers. 《深度学习简析,TensorFlow,Torch,Theano,Mxnet》 介绍:深度学习简析,TensorFlow,Torch,Theano,Mxnet. 《"Notes Essays —CS183C: Technology-enabled Blitzscaling — Stanford University》 ...
Deep Multimodal Learning: A Survey on Recent Advances and Trends The success of deep learning has been a catalyst to solving increasingly complex machine-learning problems, which often involve multiple data modalities. W... D Ramachandram,GW Taylor - 《IEEE Signal Processing Magazine》 被引量: 12...
近期在arXiv上发布出一本新的名为《Multimodal Deep Learning》,是德国的一个seminar里,好多人一起整理出来在multimodal领域里对SOTA的综述。全书272页,很综合的对这个方向的工作以及展望进行了完整的阐述,看了下,还可以,开源的书,也是免费的,推荐给大家。书的结构如下: ...