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Found 6 papers, 0 papers with code
Prediction of Malignant & Benign Breast Cancer: A Data Mining Approach in Healthcare Applications
As a potential contributor to state-of-art technology development, data mining finds a multi-fold application in predicting Brest cancer.
Learning to Clean: A GAN Perspective
We compare the performance of CycleGAN for document cleaning tasks using unpaired images with a Conditional GAN trained on paired data from the same dataset.
Residual-CNDS for Grand Challenge Scene Dataset
The outcome result from the two datasets proved our proposed model (Residual-CNDS) effectively handled the slow convergence, overfitting, and degradation.
The Compressed Model of Residual CNDS
Our proposed model trained on very large-scale MIT Places365-Standard scene datasets, which backing our hypothesis that the new compressed model inherited the best of the previous ResCNDS8 model, and almost get the same accuracy in the validation Top-1 and Top-5 with 87. 64% smaller in size and 13. 33% faster in the training time.
Residual Squeeze VGG16
This model can be implemented on almost every neural network model with fully incorporated residual learning.
Residual CNDS
In the other side, Residual Learning is another technique emerged recently to ease the training of very deep CNN.
