CNN-MRF

Reported on 3 benchmarks across 3 tasks · 1 paper · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision3 results

HyperspectralonPavia University
Overall Accuracy· 2017-05-01
96.18
best: 100 (JigsawHSI)
SOTA
Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network arXiv:1705.00727
Image ClassificationonPavia University
Overall Accuracy· 2017-05-01
96.18
best: 100 (JigsawHSI)
SOTA
Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network arXiv:1705.00727
Hyperspectral Image SegmentationonPavia University
Overall Accuracy· 2017-05-01
96.18
best: 100 (JigsawHSI)
SOTA
Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network arXiv:1705.00727