The **Adaptive Locally Connected Neuron (ALCN)** is a topology aware, and locally adaptive -focusing neuron:

$$a =  f\:\Bigg( \sum_{i=1}^{m} w_{i}\phi\left( \tau\left(i\right),\Theta\right) x_{i} + b \Bigg) %f\:\Bigg(\mathbf{X(W \circ \Phi) + b} \Bigg) $$

**YOLOv4** is a one-stage object detection model that improves on [YOLOv3](https://paperswithcode.com/method/yolov3) with several bags of tricks and modules introduced in the literature. The components section below details the tricks and modules used.

YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

ALCN

An Adaptive Locally Connected Neuron Model: Focusing Neuron

A **Depthwise Dilated Separable Convolution** is a type of [convolution](https://paperswithcode.com/method/convolution) that combines [depthwise separability](https://paperswithcode.com/method/depthwise-separable-convolution) with the use of [dilated convolutions](https://paperswithcode.com/method/dilated-convolution).

Source	An Adaptive Locally Connected Neuron Model: Focusing Neuron
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com