What is GoogLeNet architecture?
GoogLeNet is a type of convolutional neural network based on the Inception architecture. It utilises Inception modules, which allow the network to choose between multiple convolutional filter sizes in each block.
What was the main architectural feature of the GoogLeNet?
The GoogleNet Architecture is 22 layers deep, with 27 pooling layers included. There are 9 inception modules stacked linearly in total. The ends of the inception modules are connected to the global average pooling layer.
What is an inception model?
Introduction. Inception v3 is a widely-used image recognition model that has been shown to attain greater than 78.1% accuracy on the ImageNet dataset. The model is the culmination of many ideas developed by multiple researchers over the years.
Which is better AlexNet or GoogLeNet?
According to the results of the experiment, GoogLeNet training on fabric defects is faster than that of AlexNet. The performance of GoogLeNet is the best outdoing than AlexNet on various parameter including time, accuracy, dropout, and the initial learning.
What is AlexNet good for?
AlexNet is a leading architecture for any object-detection task and may have huge applications in the computer vision sector of artificial intelligence problems. In the future, AlexNet may be adopted more than CNNs for image tasks.
Is GoogleNet and inception same?
Inception V1 (or GoogLeNet) was the state-of-the-art architecture at ILSRVRC 2014. It has produced the record lowest error at ImageNet classification dataset but there are some points on which improvement can be made to improve the accuracy and decrease the complexity of the model.
What is AlexNet used for?
What is the role of inception module in GoogLeNet?
The main idea of the Inception module is that of running multiple operations (pooling, convolution) with multiple filter sizes (3×3, 5×5…) in parallel so that we do not have to face any trade-off. a max-pooling operation with a filter size of 3×3 (same reasoning with padding and stride as before).
Is inception and GoogLeNet same?
Using the dimension-reduced inception module, a neural network architecture is constructed. This is popularly known as GoogLeNet (Inception v1). GoogLeNet has 9 such inception modules fitted linearly. It is 22 layers deep (27, including the pooling layers).
Why is inception a layer?
Inception Modules are used in Convolutional Neural Networks to allow for more efficient computation and deeper Networks through a dimensionality reduction with stacked 1×1 convolutions. The modules were designed to solve the problem of computational expense, as well as overfitting, among other issues.
How many layers are there in GoogLeNet?
22 layers
The GoogLeNet architecture consists of 22 layers (27 layers including pooling layers), and part of these layers are a total of 9 inception modules(figure4).
Is ResNet better than GoogLeNet?
Through the changes mentioned, ResNets were learned with network depth of as large as 152. It achieves better accuracy than VGGNet and GoogLeNet while being computationally more efficient than VGGNet. ResNet-152 achieves 95.51 top-5 accuracies. The architecture is similar to the VGGNet consisting mostly of 3X3 filters.
What are the architectural details of GoogLeNet?
Below is Layer by Layer architectural details of GoogLeNet. The overall architecture is 22 layers deep. The architecture was designed to keep computational efficiency in mind. The idea behind that the architecture can be run on individual devices even with low computational resources.
Which is simpler GoogLeNet or vgg-16 architecture?
VGG-16 is a simpler architecture model, since its not using much hyper parameters. It always uses 3 x 3 filters with stride of 1 in convolution layer and uses SAME padding in pooling layers 2 x 2 with stride of 2. The winner of ILSVRC 2014 and the GoogLeNet architecture is also known as Inception Module.
What kind of neural network is GoogLeNet based on?
GoogLeNet was based on a deep convolutional neural network architecture codenamed “Inception”, which was responsible for setting the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC 2014). The 1-crop error rates on the ImageNet dataset with a pretrained model are list below.
How many layers are there in GoogLeNet architecture?
The GoogLeNet architecture consists of 22 layers (27 layers including pooling layers), and part of these layers are a total of 9 inception modules (figure4). The table below depicts the conventional GoogLeNet architecture.