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Action Recognition with Kernel-based Graph Convolutional Networks
Learning graph convolutional networks (GCNs) is an emerging field which ...
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Image Annotation based on Deep Hierarchical Context Networks
Context modeling is one of the most fertile subfields of visual recognit...
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End-to-end training of deep kernel map networks for image classification
Deep kernel map networks have shown excellent performances in various cl...
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Action Recognition with Deep Multiple Aggregation Networks
Most of the current action recognition algorithms are based on deep netw...
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Deep hierarchical pooling design for cross-granularity action recognition
In this paper, we introduce a novel hierarchical aggregation design that...
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Deep Context-Aware Kernel Networks
Context plays a crucial role in visual recognition as it provides comple...
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Totally Deep Support Vector Machines
Support vector machines (SVMs) have been successful in solving many comp...
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Human Action Recognition with Multi-Laplacian Graph Convolutional Networks
Convolutional neural networks are nowadays witnessing a major success in...
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Human Action Recognition with Deep Temporal Pyramids
Deep convolutional neural networks (CNNs) are nowadays achieving signifi...
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Finite State Machines for Semantic Scene Parsing and Segmentation
We introduce in this work a novel stochastic inference process, for scen...
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Canonical Correlation Analysis for Misaligned Satellite Image Change Detection
Canonical correlation analysis (CCA) is a statistical learning method th...
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Cascaded Coarse-to-Fine Deep Kernel Networks for Efficient Satellite Image Change Detection
Deep networks are nowadays becoming popular in many computer vision and ...
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Learning Explicit Deep Representations from Deep Kernel Networks
Deep kernel learning aims at designing nonlinear combinations of multipl...
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Learning Deep Context-Network Architectures for Image Annotation
Context plays an important role in visual pattern recognition as it prov...
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Graph Kernels based on High Order Graphlet Parsing and Hashing
Graph-based methods are known to be successful in many machine learning ...
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High Order Stochastic Graphlet Embedding for Graph-Based Pattern Recognition
Graph-based methods are known to be successful for pattern description a...
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