activity
20182022
most citedDeep Context-Aware Kernel Networks

2 citations · 3 across the 4 of their papers we have counts for

collaborators

6 papers

eess.IV2022

Alternative design of DeepPDNet in the context of image restoration

Mingyuan Jiu, Nelly Pustelnik

This work designs an image restoration deep network relying on unfolded Chambolle-Pock primal-dual iterations. Each layer of our network is built from Chambolle-Pock iterations whe…

cs.CV2020

Image Annotation based on Deep Hierarchical Context Networks

Mingyuan Jiu, Hichem Sahbi

Context modeling is one of the most fertile subfields of visual recognition which aims at designing discriminant image representations while incorporating their intrinsic and extri…

cs.CV20201 cited

End-to-end training of deep kernel map networks for image classification

Mingyuan Jiu, Hichem Sahbi

Deep kernel map networks have shown excellent performances in various classification problems including image annotation. Their general recipe consists in aggregating several layer…

cs.CV20192 cited

Deep Context-Aware Kernel Networks

Mingyuan Jiu, Hichem Sahbi

Context plays a crucial role in visual recognition as it provides complementary clues for different learning tasks including image classification and annotation. As the performance…

cs.CV2018

Learning Explicit Deep Representations from Deep Kernel Networks

Mingyuan Jiu, Hichem Sahbi

Deep kernel learning aims at designing nonlinear combinations of multiple standard elementary kernels by training deep networks. This scheme has proven to be effective, but intract…

cs.CV2018

Learning Deep Context-Network Architectures for Image Annotation

Mingyuan Jiu, Hichem Sahbi

Context plays an important role in visual pattern recognition as it provides complementary clues for different learning tasks including image classification and annotation. In the…