There's no single "best" layer size; the optimal size depends heavily on the specific application. The ideal layer size varies across different contexts, including 3D printing, image editing, and machine learning.
3D Printing Layer Size
In 3D printing, the optimal layer height is related to the nozzle diameter. A good rule of thumb is to keep the layer height between 25% and 80% of the nozzle diameter.
- Example: For a 0.8mm nozzle, the ideal layer height would range from 0.2mm to 0.64mm. Lower layer heights (within this range) generally result in higher print quality and detail, but increase print time. Higher layer heights reduce print time but may sacrifice detail. Sources suggest 0.12mm to 0.15mm as a great range for accuracy and detail.
Image Editing Layer Size (Canvas Size)
In image editing software, the optimal canvas size depends on the intended use and desired level of detail. Larger canvas sizes allow for more layers and higher resolution, but require more processing power and storage space. There's no universal "best" size; it's determined by the project's needs.
Machine Learning Layer Size (Neural Networks)
In machine learning, especially with Multi-Layer Perceptrons (MLPs), determining the optimal number of layers and neurons per layer is a complex process. There isn't a simple formula; it involves experimentation and optimization techniques. The optimal architecture depends on the dataset's complexity and the specific problem being solved. Rules of thumb based on input and output layer sizes exist, but these are starting points rather than definitive answers.
Other Contexts
In other contexts, such as map editing (tile layers) or circuit board design (pad sizes), layer size is determined by the specific requirements of the project. For example, aligning block sizes across multiple layers in data storage can improve performance.