Python for Computer Vision & Image Recognition – Deep Learning Convolutional Neural Network (CNN) – Keras & TensorFlow 2
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课程内容
Introduction Setting up Python and Jupyter Notebook Single Cells – Perceptron and Sigmoid Neuron Neural Networks – Stacking cells to create network Important concepts: Common Interview questions Standard Model Parameters Tensorflow and Keras Python – Dataset for classification problem Python – Building and training the Model Python – Solving a Regression problem using ANN Complex ANN Architectures using Functional API Saving and Restoring Models Hyperparameter Tuning CNN – Basics Creating CNN model in Python Analyzing impact of Pooling layer Project : Creating CNN model from scratch Project : Data Augmentation for avoiding overfitting Transfer Learning : Basics Transfer Learning in Python Congratulations & about your certificate
“Learn the latest techniques in computer vision with Python , OpenCV , and Deep Learning!”
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课程内容
Course Overview and Introduction NumPy and Image Basics Image Basics with OpenCV Image Processing Video Basics with Python and OpenCV Object Detection with OpenCV and Python Object Tracking Deep Learning for Computer Vision Capstone Project BONUS SECTION: THANK YOU!
Learn in practice everything you need to know about Computer Vision! Build projects step by step using Python!
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课程内容
Introduction Face detection Face recognition Object tracking Neural networks for image classification Convolutional neural networks for image classification Transfer learning and fine tuning Neural networks for classification of emotions Autoencoders Object detection with YOLO Recognition of gestures and actions Deep dream Style transfer GANs (Generative adversarial networks) Image segmentation Final remarks
“Transfer Learning, TensorFlow Object detection, Classification, Yolo object detection, real time projects much more..!!”
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课程内容
Introduction Starting with google colab and Gdrive Creating Your First Transfer learning model Introduction to State of Art models Model Explainability and feature-maps Introduction to object detection with Yolo Object Detection with TensorFlow Cv2 experiments Bonus Theory lectures and Exercises bonus
2020 Update with TensorFlow 2.0 Support. Become a Pro at Deep Learning Computer Vision! Includes 20+ Real World Projects
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课程内容
“Introduction Intro to Computer Vision & Deep Learning Installation Guide Handwriting Recognition OpenCV Tutorial – Learn Classic Computer Vision & Face Detection (OPTIONAL) Neural Networks Explained Convolutional Neural Networks (CNNs) Explained Build CNNs in Python using Keras What CNNs ‘see’ – Filter Visualizations, Heatmaps and Salience Maps Data Augmentation: Cats vs Dogs Assessing Model Performance Optimizers, Learning Rates & Callbacks with Fruit Classification Batch Normalization & LeNet, AlexNet: Clothing Classifier Advanced Image Classiers – ImageNet in Keras (VGG16/19, InceptionV3, ResNet50) Transfer Learning: Build a Flower & Monkey Breed Classifier Design Your Own CNN – LittleVGG: A Simpsons Classifier Advanced Activation Functions & Initializations Facial Applications – Emotion, Age & Gender Recognition Medical Imaging – Image Segmentation with U-Net Principles of Object Detection TensorFlow Object Detection API Object Detection with YOLO & Darkflow: Build a London Underground Sign Detector DeepDream & Neural Style Transfers: Make AI Generated Art Generative Adversarial Networks (GANs): Simulate Aging Faces Face Recognition with VGGFace The Computer Vision World BONUS – Build a Credit Card Number Reader BONUS – Use Cloud GPUs on PaperSpace BONUS – Create a Computer Vision API & Web App Using Flask and AWS”
“Learn OpenCV, Keras, object and lane detection, and traffic sign classification for self-driving cars”
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课程内容
Environment Setup and Installation Introduction to Self-Driving Cars Python Crash Course [Optional]Computer Vision Basics: Part 1 Computer Vision Basics: Part 2 Computer Vision Basics: Part 3 Machine Learning: Part 1 Machine Learning: Part 2 Artificial Neural Networks Deep Learning and Tensorflow: Part 1 Deep Learning and Tensorflow: Part 2 Wrapping Up
Learn Computer Vision and Image Processing From Scratch in LabVIEW and build 9 Vision-based Apps
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课程内容
Basics of LabVIEW Vision Development Module Color Processing Basic Feature Detection Lines and Edges Advanced Feature Detection Conclusion and Bonus Section
“Introduction Download Code and Setup Colab OpenCV – Image Operations OpenCV – Image Segmentation OpenCV – Haar Cascade Classifiers OpenCV – Image Analysis and Transformation OpenCV – Motion and Object Tracking OpenCV – Facial Landmark Detection & Face Swaps OpenCV Projects OpenCV – Working With Video Deep Learning in Computer Vision Introduction Building CNNs in PyTorch Building CNNs in TensorFlow with Keras Assessing Model Performance Improving Models and Advanced CNN Design Visualizing What CNN’s Learn Advamced Convolutional Neural Networks Building and Loading Advanced CNN Archiectures and Rank-N Accuracy Using Callbacks in Keras and PyTorch PyTorch Lightning Transfer Learning and Fine Tuning Google DeepStream and Neural Style Transfer Autoencoders Generative Adversarial Networks (GANs) Siamese Network Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning Object Detection Modern Object Detectors – YOLO, EfficientDet, Detectron2 Gun Detector – Scaled-YoloV4 Mask Detector TFODAPI MobileNetV2_SSD Sign Language Detector TFODAPI EfficentDet Pothole Detector – TinyYOLOv4 Mushroom Detector Detectron2 Website Region Detector YOLOv4 Darknet Drone Maritime Detector R-CNN Chess Piece YOLOv3 Bloodcell Detector YOLOv5 Hard Hat Detector EfficentDet Plant Doctor Detector YOLOv5 Deep Segmentation – U-Net, SegNet, DeeplabV3 and Mask R-CNN Body Pose Estimation Tracking with DeepSORT Deep Fakes Vision Transformers – ViTs BiT BigTransfer Classifier Keras Depth Estimation Image Similarity using Metric Learning Image Captioning with Keras Video Classification usign CNN+RNN Video Classification with Transformers Point Cloud Classification PointNet Point Cloud Segmentation Using PointNet Medical Project – X-Ray Pneumonia Prediction Medical Project – 3D CT Scan Classification Low Light Image Enhancement MIRNet Deploy your CV App using Flask RestFUL API & Web App OCR Captcha Cracker”
有数以千计的在线课程和课程可以帮助您提高 计算机视觉 技能并获得 计算机视觉 证书。