Deep Learning for Computer Vision

The Google Inception-V3 model

Inception-V3 was proposed by Szegedy et al. (https://arxiv.org/pdf/1409.4842.pdf) and introduced the concept of inception that has a better way of generalization. This was the architecture that won the ImageNet competition in 2014. It is geared towards efficiency for speed and size. It has 12 times lesser parameters than AlexNet. Inception is the micro-architecture on which a macro-architecture is built. Each hidden layer has a higher-level representation of the image. At each layer, we have an option of using pooling or other layers. Instead of using one type of kernel, inception uses several kernels. An average pooling is followed by various size convolutions and then they are concatenated.

The kernel parameters ...