A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the part of the input it is on, then summing the results into an output.

Intuitively, a convolution allows for weight sharing - reducing the number of effective parameters - and image translation (allowing for the same feature to be detected in different parts of the input space).

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Paper Code Results Date Stars


Task Papers Share
Semantic Segmentation 52 7.91%
Object Detection 44 6.70%
Image Classification 24 3.65%
reinforcement-learning 17 2.59%
Super-Resolution 14 2.13%
Quantization 14 2.13%
Medical Image Segmentation 11 1.67%
Time Series 11 1.67%
Management 9 1.37%


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign