第975回千葉医学会例会・第19回歯科口腔外科例会

<p>It can be seen that the system clearly classified the expressions classes.</p

Sensitivity for each class classification analysis on Indian Pines, Pavia University, and Pavia Centre, for both PFKNN and PSVM for all three datasets.

<p>Sensitivity for each class classification analysis on Indian Pines, Pavia University, and Pavia Centre, for both PFKNN and PSVM for all three datasets.</p

Classification maps of Pavia University (PU) with different number of training samples i.e. 5%, 10%, 15%, 20%, and 25% to train FKNN, SVM, PFKNN, and PSVM respectively.

<p>Classification maps of Pavia University (PU) with different number of training samples i.e. 5%, 10%, 15%, 20%, and 25% to train FKNN, SVM, PFKNN, and PSVM respectively.</p

Specificity for each class classification analysis on Indian Pines, Pavia University, and Pavia Centre, for both PFKNN and PSVM for all three datasets.

<p>Specificity for each class classification analysis on Indian Pines, Pavia University, and Pavia Centre, for both PFKNN and PSVM for all three datasets.</p

Classification maps of Indian Pines (IP) with different number of training samples i.e. 5%, 10%, 15%, 20%, and 25% to train FKNN, SVM, PFKNN, and PSVM respectively.

<p>Classification maps of Indian Pines (IP) with different number of training samples i.e. 5%, 10%, 15%, 20%, and 25% to train FKNN, SVM, PFKNN, and PSVM respectively.</p

Pavia Centre.

<p>Pavia Centre.</p

Indian Pines dataset.

<p>Indian Pines dataset.</p

Overall classification accuracy for PSVM, SVM, PFKNN and FKNN for both Indian Pines, Pavia University, and Pavia Centre datasets.

<p>Overall classification accuracy for PSVM, SVM, PFKNN and FKNN for both Indian Pines, Pavia University, and Pavia Centre datasets.</p

Indian Pines.

<p>Indian Pines.</p

Classification maps of Pavia Centre (PC) with different number of training samples i.e. 5%, 10%, 15%, 20%, and 25% to train PFKNN, and PSVM.

<p>Classification maps of Pavia Centre (PC) with different number of training samples i.e. 5%, 10%, 15%, 20%, and 25% to train PFKNN, and PSVM.</p