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===소스=== | ===소스=== | ||
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+ | == 메타데이터 == | ||
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+ | ===위키데이터=== | ||
+ | * ID : [https://www.wikidata.org/wiki/Q17069496 Q17069496] |
2020년 12월 26일 (토) 05:01 판
노트
위키데이터
- ID : Q17069496
말뭉치
- The data set used here is MNIST dataset as mentioned above.[1]
- Did you know you can fully train a LeNet Convolutional Neural Network model with the MNIST dataset directly on iOS devices ?[2]
- the MNIST dataset, which stands for Modified National Institute of Standards and Technology database.[3]
- The MNIST dataset is one of the most common datasets used for image classification and accessible from many different sources.[3]
- In fact, even Tensorflow and Keras allow us to import and download the MNIST dataset directly from their API.[3]
- # example of loading the fashion mnist dataset from matplotlib import pyplot from keras .[4]
- # example of loading the mnist dataset from keras .[5]
- The MNIST dataset can be online, and it is essentially a database of various handwritten digits.[6]
- The MNIST dataset has a large amount of data and is commonly used to demonstrate the real power of deep neural networks.[6]
- The MNIST dataset is a multilevel dataset consisting of 10 classes in which we can classify numbers from 0 to 9.[6]
- The major difference between the datasets that we have used before and the MNIST dataset is the method in which MNIST data is inputted in a neural network.[6]
- Building a digit classifier using MNIST dataset.[7]
- I trained a CNN (on tensorflow ) for digit recognition using MNIST dataset.[8]
- The MNIST database was constructed from NIST's Special Database 3 and Special Database 1 which contain binary images of handwritten digits.[9]
- The training 60k samples on MNIST database are trained by the SVM.[10]
- Without augmentation, experimental results of test error rate 1.03% on the test 10k MNIST database shows that proposed method is effective in handwritten digits recognition.[10]
- To train and test the CNN, we use handwriting imagery from the MNIST dataset.[11]
- In this post also we’ll use Fashion MNIST dataset.[12]
- MNIST database consists of two NIST databases – Special Database 1 and Special Database 3.[13]
- They were developed by Salakhutdinov, Ruslan and Murray, Iain in 2008 as a binarized version of the original MNIST dataset.[13]
- Kuzushiji MNIST Dataset developed by Tarin Clanuwat, Mikel Bober-Irizar, Asanobu Kitamoto, Alex Lamb, Kazuaki Yamamoto and David Ha for Deep Learning on Classical Japanese Literature.[13]
- The Fashion MNIST dataset we’re using is loaded from disk on Line 26.[14]
- Our goal is to train a classifier that will identify the digits in the MNIST dataset.[15]
- Since, our task is to detect the 10 digits in the MNIST database, the output of the network should be a vector of length 10, 1 element corresponding to each digit.[15]
- Last dense layer: There are 16 x 7 x 7 input values and it produces 10 output values corresponding to the 10 digits in the MNIST dataset.[15]
- In this article we'll build a simple convolutional neural network in PyTorch and train it to recognize handwritten digits using the MNIST dataset.[16]
- It let's use load the MNIST dataset in a handy way.[16]
- In summary we built a new environment with PyTorch and TorchVision, used it to classifiy handwritten digits from the MNIST dataset and hopefully developed a good intuition using PyTorch.[16]
- The MNIST dataset contains 70,000 images of handwritten digits (zero to nine) that have been size-normalized and centered in a square grid of pixels.[17]
소스
- ↑ A simple 2D CNN for MNIST digit recognition
- ↑ MNIST CNN Core ML Training
- ↑ 3.0 3.1 3.2 Image Classification in 10 Minutes with MNIST Dataset
- ↑ Deep Learning CNN for Fashion-MNIST Clothing Classification
- ↑ How to Develop a CNN for MNIST Handwritten Digit Classification
- ↑ 6.0 6.1 6.2 6.3 TensorFlow MNIST Dataset in CNN
- ↑ Implement CNN using Keras in MNIST Dataset.
- ↑ Poor performance on digit recognition with CNN trained on MNIST dataset
- ↑ MNIST handwritten digit database, Yann LeCun, Corinna Cortes and Chris Burges
- ↑ 10.0 10.1 Handwritten Digits Recognition by Using CNN Alex-Net Pre-trained for Large-scale Object Image Dataset
- ↑ MNIST - Create a CNN from Scratch
- ↑ Keras Example: CNN with Fashion MNIST dataset
- ↑ 13.0 13.1 13.2 6 MNIST Image Datasets That Data Scientists Should Be Aware Of (With Python Implementation)
- ↑ Fashion MNIST with Keras and Deep Learning
- ↑ 15.0 15.1 15.2 Convolutional Neural Network with MNIST — Python API for CNTK 2.6 documentation
- ↑ 16.0 16.1 16.2 MNIST Handwritten Digit Recognition in PyTorch
- ↑ 3.3. The MNIST Dataset — conx 3.7.9 documentation
메타데이터
위키데이터
- ID : Q17069496