Atrous convolution, also known as dilated convolution, is a technique used in convolutional neural networks to expand the receptive field without increasing the number of parameters or the amount of computation. It is particularly useful in tasks like semantic segmentation where capturing multi-scale context is important, as it allows for a larger field of view without downsampling the feature map resolution.

Atrous Convolution

Atrous convolution

dilated convolution

Convolutional Neural Networks (CNNs) are a class of deep neural networks primarily used for analyzing visual data, leveraging convolutional layers to automatically and adaptively learn spatial hierarchies of features. They excel in tasks such as image recognition, classification, and object detection by efficiently capturing spatial and temporal dependencies in data through shared weights and local connectivity.

convolutional neural networks

A receptive field is the specific region of sensory space in which a stimulus will modify the firing of a particular neuron, crucial for understanding how sensory systems process information. In visual systems, for example, receptive fields allow for the detection of edges, motion, and other visual features by integrating signals from photoreceptors.

receptive field

number of parameters

amount of computation

Semantic segmentation is a computer vision task that involves classifying each pixel in an image into a predefined category, enabling detailed scene understanding. It is crucial for applications like autonomous driving and medical imaging, where precise localization and identification of objects are essential.

semantic segmentation

multi-scale context

Field of view refers to the extent of the observable world that can be seen at any given moment through an optical instrument or the human eye. It is crucial in applications like photography, astronomy, and virtual reality, where it influences perception and spatial awareness.

field of view

Downsampling is like taking a big picture and making it smaller by keeping only some of the parts. It's a way to make things easier to look at or use when you don't need all the details.

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