NUST-Machine-Intelligence-Laboratory

Pinned Repositories

FECANET
Language:Python31 1 50
HFAN
Language:Python31 1 153
hsi_road
Language:Python15 3 22
HVC
Language:Python107 10 112
nsrom
Language:Python34 3 186
PKINet
Language:Python48 0 06
PNP
The source code and models for our paper PNP: Robust Learning from Noisy Labels by Probabilistic Noise Prediction
Language:Python9 1 51
RCTNet
Language:Python80
VideoMAC
Language:Python12 1 30
weblyFG-dataset
Language:Python23 2 11

NUST-Machine-Intelligence-Laboratory's Repositories

NUST-Machine-Intelligence-Laboratory/HVC
Language:Python107 10 112
NUST-Machine-Intelligence-Laboratory/PKINet
Language:Python48 0 06
NUST-Machine-Intelligence-Laboratory/HFAN
Language:Python31 1 153
NUST-Machine-Intelligence-Laboratory/weblyFG-dataset
Language:Python23 2 11
NUST-Machine-Intelligence-Laboratory/VideoMAC
Language:Python12 1 30
NUST-Machine-Intelligence-Laboratory/PNP
The source code and models for our paper PNP: Robust Learning from Noisy Labels by Probabilistic Noise Prediction
Language:Python9 1 51
NUST-Machine-Intelligence-Laboratory/RCTNet
Language:Python80
NUST-Machine-Intelligence-Laboratory/Softly-Update-Drop
Web-Supervised Network with Softly Update-Drop Training for Fine-Grained Visual Classification
Language:Python6 1 12
NUST-Machine-Intelligence-Laboratory/SSC
Language:Python6 1 01
NUST-Machine-Intelligence-Laboratory/HPAN
Language:Python5 1 02
NUST-Machine-Intelligence-Laboratory/LTFormer
51
NUST-Machine-Intelligence-Laboratory/SED
A self-adaptive and class-balanced approach to improve deep neural network performance in the presence of noisy labels
Language:Python4 0 0
NUST-Machine-Intelligence-Laboratory/Advanced-Softly-Update-Drop
This is the source code for our paper Exploiting Web Images for Fine-Grained Visual Recognition by Eliminating Open-set Noise
Language:Python3 0 00
NUST-Machine-Intelligence-Laboratory/HGPU
Language:Python30
NUST-Machine-Intelligence-Laboratory/KTSE
KTSE: a novel approach for weakly supervised semantic segmentation, addressing under-activation and over-expansion issues by simulating inter-image erasing and enhancing network localization
Language:Python3 0 0
NUST-Machine-Intelligence-Laboratory/MLCL
Language:Python3 0 0
NUST-Machine-Intelligence-Laboratory/WSNFG
This is the source code for our paper Web-Supervised Network for Fine-Grained Visual Classification
Language:Python3 1 0
NUST-Machine-Intelligence-Laboratory/CBS
2
NUST-Machine-Intelligence-Laboratory/Co-mining
Language:Python2 1 1
NUST-Machine-Intelligence-Laboratory/NPN
2
NUST-Machine-Intelligence-Laboratory/project-KTSE
KTSE: a novel approach for weakly supervised semantic segmentation, addressing under-activation and over-expansion issues by simulating inter-image erasing and enhancing network localization
2
NUST-Machine-Intelligence-Laboratory/UO-SAM
Language:Python2
NUST-Machine-Intelligence-Laboratory/Jo-SNC
Language:Python1 1 1
NUST-Machine-Intelligence-Laboratory/TorchSemiSeg2
Language:Python1 1 0
NUST-Machine-Intelligence-Laboratory/Anti-Collapse-Loss
Language:Python
NUST-Machine-Intelligence-Laboratory/dmbfgvr
This is the source code for our paper Data-driven Meta-set Based Fine-Grained Visual Recognition.
Language:Python0 0
NUST-Machine-Intelligence-Laboratory/NiCI-Pruning
NUST-Machine-Intelligence-Laboratory/NUST-Machine-Intelligence-Laboratory.github.io
Language:HTML
NUST-Machine-Intelligence-Laboratory/project-SED
A self-adaptive and class-balanced approach to improve deep neural network performance in the presence of noisy labels
Language:JavaScript
NUST-Machine-Intelligence-Laboratory/prune_and_merge
Language:Python1 0