hli1221/imagefusion_deeplearning
VggML (ICPR 2018, Beijing)
This helps image analysts combine information from two different types of photos: infrared and visible light images. It takes a pair of images – one infrared and one visible – and produces a single, enhanced image that contains critical details from both. This is ideal for professionals in fields like surveillance, remote sensing, or medical imaging who need a more comprehensive view than either image type can provide alone.
217 stars. No commits in the last 6 months.
Use this if you need to merge an infrared image and a visible light image to create one comprehensive image with more detail and clarity.
Not ideal if you are working with images other than infrared and visible light, or if you need to perform other types of image processing like object detection or segmentation.
Stars
217
Forks
74
Language
MATLAB
License
—
Category
Last pushed
Jan 10, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/hli1221/imagefusion_deeplearning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
patrick-llgc/Learning-Deep-Learning
Paper reading notes on Deep Learning and Machine Learning
magicleap/SuperGluePretrainedNetwork
SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
eric-yyjau/pytorch-superpoint
Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629
lucasb-eyer/pydensecrf
Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.
changhao-chen/deep-learning-localization-mapping
A collection of deep learning based localization models