Hichem Sahbi

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Télécom ParisTech ∙ Sorbonne Université ∙ Laboratoire d'Informatique de Paris 6

Action Recognition with Kernel-based Graph Convolutional Networks

Learning graph convolutional networks (GCNs) is an emerging field which ...
12/28/2020 ∙ by Hichem Sahbi, et al. ∙ 0 ∙ share

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Image Annotation based on Deep Hierarchical Context Networks

Context modeling is one of the most fertile subfields of visual recognit...
12/21/2020 ∙ by Mingyuan Jiu, et al. ∙ 0 ∙ share

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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...
06/26/2020 ∙ by Mingyuan Jiu, et al. ∙ 0 ∙ share

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Action Recognition with Deep Multiple Aggregation Networks

Most of the current action recognition algorithms are based on deep netw...
06/08/2020 ∙ by Ahmed Mazari, et al. ∙ 0 ∙ share

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Deep hierarchical pooling design for cross-granularity action recognition

In this paper, we introduce a novel hierarchical aggregation design that...
06/08/2020 ∙ by Ahmed Mazari, et al. ∙ 0 ∙ share

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Deep Context-Aware Kernel Networks

Context plays a crucial role in visual recognition as it provides comple...
12/29/2019 ∙ by Mingyuan Jiu, et al. ∙ 15 ∙ share

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Totally Deep Support Vector Machines

Support vector machines (SVMs) have been successful in solving many comp...
12/12/2019 ∙ by Hichem Sahbi, et al. ∙ 0 ∙ share

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Human Action Recognition with Multi-Laplacian Graph Convolutional Networks

Convolutional neural networks are nowadays witnessing a major success in...
10/15/2019 ∙ by Ahmed Mazari, et al. ∙ 0 ∙ share

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Human Action Recognition with Deep Temporal Pyramids

Deep convolutional neural networks (CNNs) are nowadays achieving signifi...
05/02/2019 ∙ by Ahmed Mazari, et al. ∙ 0 ∙ share

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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...
12/27/2018 ∙ by Hichem Sahbi, et al. ∙ 0 ∙ share

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Canonical Correlation Analysis for Misaligned Satellite Image Change Detection

Canonical correlation analysis (CCA) is a statistical learning method th...
12/21/2018 ∙ by Hichem Sahbi, et al. ∙ 0 ∙ share

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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 ...
12/21/2018 ∙ by Hichem Sahbi, et al. ∙ 0 ∙ share

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Learning Explicit Deep Representations from Deep Kernel Networks

Deep kernel learning aims at designing nonlinear combinations of multipl...
04/30/2018 ∙ by Mingyuan Jiu, et al. ∙ 0 ∙ share

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Learning Deep Context-Network Architectures for Image Annotation

Context plays an important role in visual pattern recognition as it prov...
03/23/2018 ∙ by Mingyuan Jiu, et al. ∙ 0 ∙ share

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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 ...
02/28/2018 ∙ by Anjan Dutta, et al. ∙ 0 ∙ share

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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...
02/01/2017 ∙ by Anjan Dutta, et al. ∙ 0 ∙ share

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Hichem Sahbi

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