Face and Facial Keypoints Detection
Details of the Project Parts The details of the implementation parts can be seen from the steps below. Part 1 : Using OpenCV for image pre-processing, and face detection Step 0: Detect Faces Using a Haar Cascade Classifier Step 1: Add Eye Detection Step 2: De-noise an Image for Better Face Detection Step 3: Blur an Image and Perform Edge Detection Part 2 : Training a Convolutional Neural Network (CNN) to detect facial keypoints Step 5: Create a CNN to Recognize Facial Keypoints Step 6: Compile and Train the Model Step 7: Visualize the Loss Part 3 : Putting parts 1 and 2 together to identify facial keypoints on any image Step 8: Build a Robust Facial Keypoints Detector
Thanks for being here on my profile! ✅ I have 8+ years of experience. I want to serve you with my skills and I am sure you will be satisfied. I have been working on the following projects: ✅ Classification ✅ Regression ✅ Clustering ✅ Dimensionality Reduction ✅ Prediction ✅ Recognition ✅ Time Series Forecasting ✅ Recommender Systems ✅ Sentiment Analysis ✅ NLP(Natural Language Processing) ✅ Big Data Visualisation ✅ Data Mining ✅ Data Analysis ✅ Data warehousing ✅ Data Modelling ✅ So on. . . ✅ I would like to work for all kinds of Deep Learning/Machine Learning/Artificial Intelligence/Data Science projects.