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[IEEE TGRS 2018] Spectral-Spatial Unified Networks for Hyperspectral Image Classification

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Hi, I would like to get the parameters used for the KSC and Indian Pines datasets if possible.

how to modify the following code for Indian Pines? because Pavia University dataset has 9 class and Indian Pines 16. w=2 num_PC=1 israndom=True randtime = 1 OASpectral_IP = np.zeros((9+2,randtime)) s1s2=1...

Hello, I want to get the code of comparative Ablation Experiment in the paper, is that ok

Dear Yonghao. I am getting the error "The `pool_size` argument must be a tuple of 2 integers. Received: (1, 2, 2)" while using your function MCNN_RS.

Dear Yonghao, can you please tell me how did you choose the values of train_num_array for different datasets in HyperspectralSamples function. What is the significance of those values.

Dear YonghaoXu, can you please clarify the use of s1s2 =1 and s1s2=2 in HyperspectralSamples function of HyperFunctions module.

labels=sio.loadmat("Indian_pines_gt.mat")['indian_pines_gt'] palette=np.array([[255,0,0],[0,255,0],[0,0,255],[255,255,0],[0,255,255],[255,0,255],[176,48,96],[46,139,87],[160,32,240],[255,127,80],[127,255,212],[218,112,214],[160,82,45],[127,255,0],[216,191,216],[238,0,0]]) palette=palette*1.0/255 X_result=np.zeros((labels.shape[0],3)) num_class=labels.max() or i in range(0,num_class): X_result[np.where(labels==i),0]=palette[i,0] X_result[np.where(labels==i),1]=palette[i,1] X_result[np.where(labels==i),2]=palette[i,2] X_result=np.reshape(X_result,(145,145,3)) I am getting the following error, ValueError: cannot reshape array of size 435 into shape (145,145,3)

Thank you sharing the code. Could you please give me an insight of "MirrowCut function" in HyperFunctions.py file?

Hello Dear ! I wan to know how you extract the feature from layers? suppose if we have shape (145,145,30) so how we can extract features from this type of...