A comprehensive review and analysis of deep learning
Posted: Thu Feb 06, 2025 3:17 am
AlexNet is a neural network model developed by three scientists, Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton. It consists of five convolutional layers and three fully connected layers, and uses ReLU nonlinear activation functions and Dropout, as well as GPU acceleration technology for training. In the ImageNet Challenge, AlexNet was trained on more than 1 million images, including 1,000 objects of different categories, and finally achieved an error rate of 15.3%, nearly 10 percentage points lower than the second place.
The success of AlexNet not only broke the historical record in the field of computer vision, but also marked the beginning of the practical application of deep learning technology. With the continuous development lithuania mobile database of deep learning technology, it has made significant progress in computer vision, natural language processing, speech recognition and other fields, and has replaced traditional machine learning methods in many fields, becoming one of the most advanced artificial intelligence technologies.
In 2012, the development of deep learning technology entered a new stage. In the same year, Yoshua Bengio, Aaron Courville, Pascal Vincent and others published a paper titled "Representation Learning: A Review and New Perspectives", which comprehensively reviewed and analyzed deep learning.
The success of AlexNet not only broke the historical record in the field of computer vision, but also marked the beginning of the practical application of deep learning technology. With the continuous development lithuania mobile database of deep learning technology, it has made significant progress in computer vision, natural language processing, speech recognition and other fields, and has replaced traditional machine learning methods in many fields, becoming one of the most advanced artificial intelligence technologies.
In 2012, the development of deep learning technology entered a new stage. In the same year, Yoshua Bengio, Aaron Courville, Pascal Vincent and others published a paper titled "Representation Learning: A Review and New Perspectives", which comprehensively reviewed and analyzed deep learning.