Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), and the Internet. The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The...
Fig. 2. An overview of our network architecture for COVID-19 diagnosis (best viewed in colour). Each augmented CT image is fed into the pre-trained periphery-aware encoder, generating representations in de-dimension. A classifier is learned on top of the representations for pneumonia classificati...
9.A non-transitory computer readable medium comprising computer code, executable by one or more processors to:obtain geometric information associated with a physical environment of a communication device participating in a multi-user communication session;determine an activity type for the multi-user comm...
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1.3 Basic Ideas of Representation Learning In this book, we focus on the distributed representation scheme (i.e., embedding), and talk about recent advances of representation learning methods for multiple lan- guage entries, including words, phrases, sentences, and documents, and their closely ...
Recent years have witnessed the emergence of deep learning-based methods as potentially useful tools for predicting molecular properties, primarily due to their remarkable capability of automatically extracting effective features from simple input data. Notably, a diverse range of neural network architectures...
General Facial Representation Learning in a Visual-Linguistic Manner Yinglin Zheng1* Hao Yang2* Ting Zhang2 Jianmin Bao2 Dongdong Chen3 Yangyu Huang2 Lu Yuan3 Dong Chen2 Ming Zeng1² Fang Wen2 1School of Informatics, Xiamen Unversity 2Microsoft Research Asi...
One may also find many approaches from the network science community in the field of community detection [57, 58], and in particular multiscale community detection [59–61]. All these methods are concerned with providing a multiresolution description of the graph structure, but do not consider ...
To further bridge the gap between clip-level and video-level representations, we intuitively introduce a learning objective to model temporal order dependency between local clips and global video. In particular, we have access to the temporal order of the sampled clips in accordance with the croppin...
Recent years have witnessed the emergence of deep learning-based methods as potentially useful tools for predicting molecular properties, primarily due to their remarkable capability of automatically extracting effective features from simple input data. Notably, a diverse range of neural network architectures...