목록alexnet (3)

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Developing and training the AlexNet model using Tensorflow on CIFAR-10 dataset

1. import libraries import tensorflow as tf from tensorflow.keras import datasets, layers, models, optimizers, regularizers 2. Load and preprocess CIFAR-10 dataset (train_images, train_labels), (test_images, test_labels) = datasets.cifar10.load_data() train_images, test_images = train_images / 255.0, test_images / 255.0 num_train = int(len(train_images) * 0.8) train_images, validation_images = t..
AI, ML 2023. 4. 11. 02:20
Developing and training the AlexNet model using PyTorch on the CIFAR-10 dataset

PyTorch model code based on "ImageNet Classification with Deep Convolutional Neural Networks" paper 1. Library import import torch import torch.nn as nn import torch.optim as optim import torchvision import torchvision.transforms as transforms from tqdm import tqdm 2. AlexNet Network class AlexNet(nn.Module): def __init__(self): super(AlexNet, self).__init__() self.features = nn.Sequential( nn.C..
AI, ML 2023. 4. 10. 01:10
[Review] ImageNet Classification with Deep Convolutional Neural Networks

ImageNet Classification with Deep Convolutional Neural Networks 알렉스넷(AlexNet)으로 유명한 CNN 네트워크를 소개한 논문입니다. 1. Introduction This paper presents the AlexNet architecture, which uses a combination of convolutional and fully-connected layers to effectively classify images. Prior to the development of this neural network, deep learning faced challenges due to insufficient datasets and computing resourc..
AI, ML 2023. 4. 10. 00:41
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