convolutional

the convolutional neural network achieved high accuracy on the image classification task.

we used a 3x3 convolutional filter to extract features from the input image.

the convolutional layer is a key component of many modern deep learning architectures.

applying a convolutional operation involves sliding the filter across the input data.

the convolutional layer learned to detect edges and corners in the images.

we performed a convolutional operation to reduce the dimensionality of the data.

the architecture included multiple convolutional blocks for improved feature extraction.

the convolutional layer's output is a feature map representing detected patterns.

we experimented with different convolutional filter sizes to optimize performance.

the convolutional layer effectively captured spatial hierarchies in the data.

the model utilized a series of convolutional and pooling layers.