Improving correlation method with convolutional neural networks
arXiv:2004.09430v1
Originality Synthesis-oriented
AI Analysis
This work addresses classification accuracy in correlation-based methods, but it appears incremental as it combines existing techniques (CNNs with correlation filters).
The authors tackled the problem of classifying correlation responses from correlation filters by introducing a convolutional neural network, which improved classification accuracy and achieved invariance to image classes and parameters.
We present a convolutional neural network for the classification of correlation responses obtained by correlation filters. The proposed approach can improve the accuracy of classification, as well as achieve invariance to the image classes and parameters.