An example of perturbed images. (a) A randomly selected image from the ImageNet dataset [10], which is labelled as the “ostrich” category and can be correctly identified by the ResNet101 [11] classification m
- [ ] MLP training is almost instant, but KAN train slow on start # TODO/Ideas: - [x] Base structure - [x] KAN simple implementation - [x] KAN trainer - [x] train KAN on test dataset - [ ] remove unnecessary dependencies in requirements.txt - [ ] test update_grid and "Other ...
During the prediction phase, our method first classifies dynamic and static activity using the first-stage abstract activity recognition model, and then proceeds to test data sharpening. After the test data is sharpened, our approach inputs the sharpened test data into the relevant second-stage ...
A HSI dataset contains 𝑀M training samples 𝑋𝑡𝑟𝑎𝑖𝑛={𝑥1,⋯,𝑥𝑚,⋯,𝑥𝑀}Xtrain={x1,⋯,xm,⋯,xM} in an ℝ𝑑×1ℝd×1 feature space, where 𝑑d is the number of spectral bands, and 1≤𝑚≤𝑀1≤m≤M. The class label of training samples ...
A HSI dataset contains 𝑀M training samples 𝑋𝑡𝑟𝑎𝑖𝑛={𝑥1,⋯,𝑥𝑚,⋯,𝑥𝑀}Xtrain={x1,⋯,xm,⋯,xM} in an ℝ𝑑×1ℝd×1 feature space, where 𝑑d is the number of spectral bands, and 1≤𝑚≤𝑀1≤m≤M. The class label of training samples ...