Caffe

Caffe is designed for speed and modularity, making it ideal for deep learning research and applications. It supports various model architectures and provides a straightforward interface for users.

Key Features

• Highly optimized for performance and speed
• Supports a wide range of neural network architectures
• Modular design allows for easy customization
• Pre-trained models available for quick deployment
• C++ and Python interfaces for flexibility
• Community-driven with extensive documentation

Pros

• Fast training times compared to other frameworks
• Rich ecosystem of pre-trained models
• Strong community support and resources
• Flexible configurations with prototxt files

Cons

• Steeper learning curve for beginners
• Limited support for more recent neural network architectures
• Less intuitive compared to some modern alternatives
• Fewer built-in tools for deployment compared to competitors