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Found 10 papers, 3 papers with code
Multiclass classification for multidimensional functional data through deep neural networks
The intrinsically infinite-dimensional features of the functional observations over multidimensional domains render the standard classification methods effectively inapplicable.
Robust Deep Neural Network Estimation for Multi-dimensional Functional Data
For any multi-dimensional functional data, we provide the uniform convergence rates for the proposed robust deep neural networks estimators.
Deep Neural Network Classifier for Multi-dimensional Functional Data
We propose a new approach, called as functional deep neural network (FDNN), for classifying multi-dimensional functional data.
Multimodal perception for dexterous manipulation
Due to the complementary properties between visual and tactile senses, it is desirable for us to combine vision and touch for a synergistic perception and manipulation.
Vision-Guided Active Tactile Perception for Crack Detection and Reconstruction
In recent years, computer vision techniques have been applied in detecting cracks in concrete structures.
Estimation of the Mean Function of Functional Data via Deep Neural Networks
In this work, we propose a deep neural network method to perform nonparametric regression for functional data.
Spatio-temporal Attention Model for Tactile Texture Recognition
Recently, tactile sensing has attracted great interest in robotics, especially for facilitating exploration of unstructured environments and effective manipulation.
Deep Multi-view Learning to Rank
We study the problem of learning to rank from multiple information sources.
Neural Class-Specific Regression for face verification
Face verification is a problem approached in the literature mainly using nonlinear class-specific subspace learning techniques.
Generalized Multi-view Embedding for Visual Recognition and Cross-modal Retrieval
In this paper, the problem of multi-view embedding from different visual cues and modalities is considered.
