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evaluate fusion pretraining on s1 or s2 by zero padding.
taeil updated
3 years ago
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Hi,
I am using the code from "[3B_tile-based_classification_with_EuroSAT_data]" in an own jupyter notebook to classify a sentinel scene.
I've used your Sentinel-Data "S2A_MSIL1C_20210331T100021_N03…
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Based on several posts that have been generated during the last few months and carrying out new tests with various mobile devices on Android, we have detected a problem with the polygons campled to gr…
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This will probably line up with the classification task. #37
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Hi, thank you for sharing this brilliant automl tool!I wish I could implement your code, but in most industry scene tasks are complicated and will not be able to be solved by classification.
When …
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I used the siamese_rpn_r50_20e_lasot_20220420_181845-dd0f151e.pth to inference the demo_sot.py. But when object misses in the
screen, the tracker will track other object which is similar to the orig…
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hi thanks for open-sourcing this wonderful , i have the following queries
1. can we additional head called object_features which classifies the features of the detected objects eg car: type of ca…
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https://github.com/HuaizhengZhang/scene-recognition-pytorch1.x-tf2.x
I have retrained many models by using pytorch 1.4 based on python3.7.
Anyone interested in using scene classification models …
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# Review-2019.6.10-彭晓婷
## Preview
- 看了论文《Semisupervised Scene Classification for Remote Sensing Images_ A Method Based on Convolutional Neural Networks and Ensemble Learning》 和《Cost-Sensitive Le…
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In the DETR model, the query tokens are used in the decoder part only, however, in VIDT the query tokens are also used for at the backbone. What is the reason behind this and what would happen if you …