Best architecture for object recognition

Question

I'm evaluating the options of using HTM (hierarchical temporal memory) and CNN (convolutional neural network) for object recognition. Which architecture (model) would is most appropriate in this case?

Answer 1

Convolutional Neural Network and its variants are best tool for object recognition . You can try with AlexNet,VGGNEt, ResNet, Batch Normalization , Dropout etc.

Answer 2

Always prefer using pretrained models and using transfer learning first in these cases. You can check out the implementation of Inception V3 etc. for object detection on tensorflow website and use them for transfer learning for your project.