Character recognition using LeNet-5
A deep model (LeNet-5) trained on the MNIST dataset is used for character recognition.
이 제출물을 팔로우합니다
- 팔로우하는 게시물 피드에서 업데이트를 확인할 수 있습니다
- 정보 수신 기본 설정에 따라 이메일을 받을 수 있습니다
The LeNet-5 model implemented in this project has 3 convolutional layers and 2 fully-connected layers. It has 62,000 training parameters, and the image input size is 32*32. This model achieved 98.48% accuracy on the MNIST test set after training on its train set. MNIST is a dataset of handwritten digits with 70,000 centred fixed-size grey-scale images. More details about the dataset are available in:
http://yann.lecun.com/exdb/mnist
Run the GUI and select your image.
인용 양식
Ebrahimi, Amir, et al. “Convolutional Neural Networks for Alzheimer’s Disease Detection on MRI Images.” Journal of Medical Imaging, vol. 8, no. 02, SPIE-Intl Soc Optical Eng, Apr. 2021, doi:10.1117/1.jmi.8.2.024503.
도움
도움 받은 파일: Pre-trained 2D LeNet-5
| 버전 | 퍼블리시됨 | 릴리스 정보 | Action |
|---|---|---|---|
| 1.0.1 | The relevant paper is published. |
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| 1.0.0 |
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