Free Coupon Discount - Modern Computer Vision™ OpenCV4, Tensorflow, Keras & PyTorch | Udemy
Using Python Learn OpenCV4, CNNs, Detectron2, YOLOv5, GANs, Tracking, Segmentation, Face Recognition & Siamese Networks, Welcome to Modern Computer Vision™ Tensorflow, Keras & PyTorch! · Computer vision applications involving Deep Learning are booming! · This course, Welcome to Modern Computer Vision™ Tensorflow, Keras & PyTorch! AI and Deep Learning are transforming industries and one of the most, Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications [Ayyadevara, V Kishore, Reddy.
- Created by Rajeev D. Ratan
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What you'll learn Modern Computer Vision™ OpenCV4, Tensorflow, Keras & PyTorch
- All major Computer Vision theory and concepts!
- Learn to use PyTorch, TensorFlow 2.0 and Keras for Computer Vision Deep Learning tasks
- OpenCV4 in detail, covering all major concepts with lots of example code
- All Course Code works in accompanying Google Colab Python Notebooks
- Learn all major Object Detection Frameworks from YOLOv5, to R-CNNs, Detectron2, SSDs, EfficientDetect and more!
- Deep Segmentation with U-Net, SegNet and DeepLabV3
- Understand what CNNs 'see' by Visualizing Different Activations and applying GradCAM
- Generative Adverserial Networks (GANs) & Autoencoders - Generate Digits, Anime Characters, Transform Styles and implement Super Resolution
- Training, fine tuning and analyzing your very own Classifiers
- Facial Recognition along with Gender, Age, Emotion and Ethnicity Detection
- Neural Style Transfer and Google Deep Dream
- Transfer Learning, Fine Tuning and Advanced CNN Techniques
- Important Modern CNNs designs like ResNets, InceptionV3, DenseNet, MobileNet, EffiicentNet and much more!
- Tracking with DeepSORT
- Siamese Networks, Facial Recognition and Analysis (Age, Gender, Emotion and Ethnicity)
- Image Captioning, Depth Estimination and Vision Transformers
- Point Cloud (3D data) Classification and Segmentation
- Making a Computer Vision API and Web App using Flask