Yijin Wang

AlexNet addressed the challenges of applying Convolutional Neural Networks (CNNs) to high-resolution images in the ImageNet dataset, which contains over 15 million labeled images across 22,000 categories. The architecture consists of eight layers, including five convolutional and three fully connected layers, and incorporates innovative techniques such as Rectified Linear Units (ReLU) for faster training, multi-GPU training to manage memory limitations, and overlapping pooling to improve resistance to overfitting.