|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-deep-learning-facial-masked-face-detection-recognition/
课程评论：没有评论
课程名称：深度学习：口罩人脸检测与识别 课程概述：深度学习是人工智能（AI）中一项令人兴奋的未来科技，正迅速发展。口罩人脸识别是一个引人注目的主题，包含多种AI技术，包括分类、SSD物体检测、MTCNN、FaceNet、数据准备、数据清洗、数据增强和训练技巧等。在新冠疫情期间，佩戴口罩已成为人们的日常要求，而传统的FaceNet模型在缺少面部信息的情况下几乎无法识别面孔，即使是iPhone或iPad的FaceID也只能在人脸未被遮挡时正常工作。在本课程中，我将教你如何训练一个适用于佩戴口罩的模型。最终展示中，学员将能够实现实时人脸检测、口罩检测和人脸识别，哪怕是戴着口罩的情况下！ 课程使用Windows操作系统，因此无须预先学习Linux。学员需要具备Python和Tensorflow的基础知识。我的教学将通过简单的概念或实际示例来解释复杂的理论和公式。模型训练通常需要大量时间，比如这个项目就需要超过400,000张图像进行训练。我会提供一些训练技巧，以加速模型训练过程，这些技巧不仅适用于人脸识别，也可以应用于未来的项目中。所有讲座均使用简单的英语进行，如果觉得讲解速度较慢，可以通过设置调整播放速度。如果不想自行训练模型，课程中还包括源代码和训练好的权重文件！除了训练步骤，这也是一个高度集成的应用。通过这个主题的学习，学员将获得技能提升。我希望你能享受AI带来的乐趣。
Deep Learning of artificial intelligence(AI) is an exciting future technology with explosive growth.Masked face recognition is a mesmerizing topic which contains several AI technologies including classifications, SSD object detection, MTCNN, FaceNet, data preparation, data cleaning, data augmentation, training skills, etc.Nowadays, people are required to wear masks due to the COVID-19 pandemic.The conventional FaceNet model barely recognizes faces without masksEven the FaceID on iPhone or iPad devices only works without masks.In this course, I will teach you how to train a model that works with masks.In the final presentation, you will be able to perform the real time face detection, face mask detection, and face recognition, even with masks!Windows is the operating system so you don't need to learn Linux first.Having Python and Tensorflow knowledge are required. In my tutorials, I would like to explain difficult theories and formulas by easy concepts or practical examples. Model training always takes a lot of time. Take this project as an example, it needs more than 400,000 images to train. I will offer training skills to speed up the training process. These training skills can be not only applied in face recognition but also in your future projects.All lectures are spoken in plain English. If you feel my speaking pace is quite slow, you can use the gear setting to speed up.If you don't want to train the model by yourself, the source code and trained weight files are included! Besides the training steps, this is also a highly integrated application.Achievement from the topic, skills grow from the project. I hope you enjoy the fun of AI.
