In use of motion atoms and motion phrases, we construct the middle-level feature representations in multi-view daily actions. A multi-view unsupervised discriminative clustering method is proposed for constructing motion atoms, and the classification accuracy of motion atoms is improved by jointly ...
Multi-Head Multi-Layer Attention to Deep Language Representations for Grammatical Error Detection 来自 arXiv.org 喜欢 0 阅读量: 159 作者:M Kaneko,M Komachi 摘要: It is known that a deep neural network model pre-trained with large-scale data greatly improves the accuracy of various tasks, ...
The advantages of such networks are that their internal representations in the hidden layers are clearly interpretable, and well-defined classification rules can be easily obtained, that calculations for classifications after training are very simple, and that they are easily implementable in hardware. ...
Based on reconstruction, we learn the latent representation by enforcing it to be close to different view-specific subspace representations, which implicitly co-regularizes subspace structures of all views to be consistent to each other. With the introduction of neural networks, more general relationsh...
Hinton, R. Williams Learning internal representations by error propagation Parallel Dist. Proc., MIT Press (1986), pp. 318-362 Google Scholar Cited by (191) Machine learning for pore-water pressure time-series prediction: Application of recurrent neural networks 2021, Geoscience Frontiers Show ...
.Thispaperproposesanoveldomainadaptationmethodforrollingbearingfaultdiagnosisbasedondeeplearningtechniques.Adeepconvo-lutionalneuralnetworkisusedasthemainarchitecture.Themulti-kernelmaximummeandiscrepancies(MMD)betweenthetwodomainsinmultiplelayersaremini-mizedtoadaptthelearnedrepresentationsfromsupervisedlearninginthesource...
By applying attention mechanism, we fuse multiple layers of features to obtain image representations that are both richly detailed and text-aligned.PerformanceResults on General Multimodal BenchmarksPerformance comparison of different model sizes. (left) Compared with 7B models including Qwen-VL-Chat, ...
These two extensions enable additional features not covered in the first version of the HEVC standard such as spatial, fidelity, bitdepth, and color gamut scalability, as well as stereoscopic and multiview representations. In this paper, we propose a software parallel decoder architecture for the ...
More specifically, DBN can learn internal representations from the input data (higher layers capture complex statistical structures) and make inferences quickly (hidden layers state computation). Although DBN can effectively learn the object features in an unsupervised manner, this model has difficulty ...
Visibility graph (VG) algorithm is an effective approach for transforming time series into complex network representations, which has recently attracted great interest. In the framework of the standard visibility graph (VG), the non-zero entries of A correspond to two time points ti and tjwhich ...