Description
Face, Age, Gender, Emotion Recognition Using Facenet Model is a course on face recognition technology with Facenet published by Udemy Online Academy. It covers implementing the Facenet model for face recognition, age estimation, gender classification, and emotion detection using machine learning techniques. Students will work with Python, TensorFlow, OpenCV, and deep learning frameworks to train and deploy models capable of real-time face analysis. The course covers preprocessing techniques, dataset management, feature extraction, and model fine-tuning to increase accuracy.
With facial recognition technology becoming increasingly important in security, healthcare, marketing, and entertainment, this course will equip you with the skills to design and implement systems capable of face recognition, age prediction, gender detection, and emotion detection. Whether you are a developer, data scientist, student, or AI enthusiast, this course will take you from the basics to the advanced level and ensure you have the confidence to use these technologies in real-world scenarios. In the end, individuals will have practical experience in building intelligent facial recognition systems with multiple features.
What you will learn in Face, Age, Gender, Emotion Recognition Using Facenet Model:
- Learn the basics of facial recognition technology and its applications
- Extract age, gender, and emotion data from images and video streams
- Process and analyze real-time data using DeepFace for practical applications
- Test and deploy the system in real-world scenarios
- And…
Course specifications
Publisher: Udemy
Instructors: ARUNNACHALAM SHANMUGARAAJAN
Language: English
Level: Intermediate
Number of Lessons: 6
Duration: 1 hours
Course topics
Face, Age, Gender, Emotion Recognition Using Facenet Model Prerequisites
Basic Python & Deep Learning Concepts Required
Pictures
Face, Age, Gender, Emotion Recognition Using Facenet Model introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Download link
File password (s): www.downloadly.ir
Size
585 MB