A neural network activation function is a function that is applied to the output of a neuron. Learn about different types of activation functions and how they work.| www.v7labs.com
Learn about the different types of neural network architectures.| www.v7labs.com
What is Mean Average Precision (mAP), how to calculate it, and why is it important for evaluating your model's performance? Read on to find out and start training your own AI models on V7 today.| www.v7labs.com
Convolutional neural networks (CNN) are particularly well-suited for image classification and object detection. Learn the basics of CNNs and how to use them.| www.v7labs.com
A list of computer vision datasets, including image classification, object detection, and semantic segmentation.| www.v7labs.com
We trained a large, deep convolutional neural network to classify the 1.3 million high-resolution images in the LSVRC-2010 ImageNet training set into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 39.7\% and 18.9\% which is considerably better than the previous state-of-the-art results. The neural network, which has 60 million parameters and 500,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and t...| papers.nips.cc