Convolutional Neural Network
A deep learning architecture designed for processing grid-like data (images) using convolutional layers that learn spatial hierarchies.
Related Concepts
- Computer Vision: Explore how Computer Vision relates to Convolutional Neural Network
- Convolution: Explore how Convolution relates to Convolutional Neural Network
- Pooling: Explore how Pooling relates to Convolutional Neural Network
- Feature Map: Explore how Feature Map relates to Convolutional Neural Network
Why It Matters
Understanding Convolutional Neural Network is crucial for anyone working with neural networks & deep learning. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
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Related Terms
Computer Vision
The field of AI focused on enabling computers to understand and interpret visual information from images and videos.
Convolution
A mathematical operation that applies filters/kernels to input data to extract features like edges, textures, and patterns.
Feature Map
The output of applying a convolutional filter to an input, representing detected features at various spatial locations.
Pooling
A down-sampling operation in CNNs that reduces spatial dimensions while retaining important features (max pooling, average pooling).