Deep Learning Practice 65-Construction of the face detection model LFFD, a detailed introduction to the architecture and principles of the LFFD model

Hello everyone, I am Wei Xue AI. Today I will introduce to you the construction of deep learning practice 65-face detection model LFFD, and a detailed introduction to the architecture and principles of the LFFD model. The LFFD (Light and Fast Face Detector) model is a deep learning model for face detection, which is designed to achieve lightweight and fast face detection. This article will introduce in detail the definition, advantages, principles, structure, training process and prediction process of the LFFD model.
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1 Introduction

1.1 What is the LFFD model?

The LFFD model is a face detection model based on deep learning technology. Its main goal is to reduce the size of the model as much as possible and increase the detection speed while maintaining high accuracy. The LFFD model adopts a series of optimization strategies and network structure design, allowing it to quickly and efficiently perform face detection in resource-limited environments such as embedded devices and mobile terminals, and is suitable for various real-time application scenarios.

1.2 Advantages and characteristics of LFFD model

LFFD model has the following advantages and characteristics:
Lightweight design: LFFD model adopts lightweight network structure and parameter configuration. This makes the model smaller and suitable for deployment on resource-constrained devices.
Fast detection: The LFFD model is optimized for real-time application scenarios. It has fast face detection speed and can complete the input image in a short time. Localization and recognition of human faces.
High accuracy: Despite the pursuit of lightweight and fast, the LFFD model still maintains high face detection accuracy and can perform in various complex scenes. effectively recognize faces.

2. Theory of LFFD model

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