"Convolutional" Example Sentences
1. The convolutional neural network did a great job of classifying the images.
2. The feature map was created using a convolutional layer.
3. The convolutional filter was designed to detect edges in the image.
4. The convolutional network was trained on a large dataset of cat and dog images.
5. The researchers used a convolutional approach to analyze the brain activity.
6. The convolutional architecture improved the accuracy of the image recognition system.
7. The convolutional layer was added to the network to increase its depth.
8. The convolutional kernel was designed to recognize specific patterns in the image.
9. The convolutional network was used to generate captions for the images.
10. The convolutional operator mapped the input to the output using a filter.
11. The purpose of the convolutional layer was to extract the features from the input.
12. The convolutional network was trained using the backpropagation algorithm.
13. The researchers used a convolutional neural network to classify the emotions in the speech.
14. The convolutional filter was designed to detect the presence of a face in the image.
15. The convolutional network was used in medical imaging to detect tumors.
16. The convolutional neural network was used to predict the outcome of a basketball game.
17. The convolutional layer was added to the network to reduce the size of the input.
18. The convolutional kernel was optimized using a genetic algorithm.
19. The researchers used a convolutional neural network to classify the music genre.
20. The convolutional operator was applied to the input to generate the output.
21. The convolutional architecture was used in natural language processing to detect sentiment.
22. The purpose of the convolutional filter was to blur the input image.
23. The convolutional network was used to generate realistic 3D models from 2D images.
24. The convolutional layer was designed to preserve spatial information in the image.
25. The convolutional kernel was used to detect the texture of the surface in the image.
26. The researchers used a convolutional neural network to recognize the handwriting in the document.
27. The convolutional operator was used in audio processing to detect the presence of specific sounds.
28. The convolutional architecture was used in speech recognition to improve the accuracy.
29. The convolutional filter was used to remove the noise from the image.
30. The convolutional network was used to diagnose diseases from medical images.
Common Phases
1.
Convolutional neural network has become a popular approach in deep learning.
2. The
convolutional layer in a CNN applies a filter to the input image.
3. The output of a
convolutional layer is known as a feature map.
4.
Convolutional networks are often used for image classification tasks.
5. The pooling layer in a CNN reduces the spatial dimensions of the feature maps.
6.
Convolutional networks can also be applied to natural language processing tasks.
7. A pretrained
convolutional network can be fine-tuned on a specific dataset for transfer learning.
8. One common modification to the CNN architecture is the use of skip connections.
9. A
convolutional autoencoder can be used for unsupervised feature learning.
10. The use of dilated convolutions in a CNN can increase the receptive field without sacrificing resolution.