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This book provides a detailed introduction to deep learning development using PaddlePaddle, covering the entire process from environment setup to practical project applications. The content includes e

MTCNN is a multi-task convolutional neural network (CNN) for face detection, consisting of three networks: P-Net, R-Net, and O-Net. P-Net generates candidate windows; R-Net performs high-precision fil

This project is a deep learning-based face age and gender recognition system. It uses OpenCV and MTCNN (Multi-Task Cascaded Convolutional Network) for face detection, along with a pretrained model for

This document introduces a CRNN text recognition model implemented using PaddlePaddle 2.0 dynamic graph. The model extracts features through CNN, performs sequence prediction via RNN, and uses CTC Los

Your code has covered most aspects of the CAPTCHA recognition project, including data processing, model training, and inference. Below are some suggestions for improvements and enhancements to your pr

Thank you for your detailed introduction! To further help everyone understand and use this CTC-based end-to-end Chinese-English speech recognition model, I will supplement and improve it from several

This project is mainly an image classifier based on TensorFlow Lite, which can achieve real-time image recognition on Android devices. Its main functions and implementation steps are as follows: ###

This is a detailed guide on how to implement image classification in an Android application. You have successfully used TensorFlow Lite for image classification and demonstrated how to obtain input da

This paper introduces the method of implementing face detection, key point detection, and mask detection in Android applications using Paddle Lite. The core code is only one line: calling `FaceDetecti

This code implements a deep learning-based face recognition system using the InsightFace framework. It includes functions for face detection, feature extraction, and face recognition, and also provide