課程摘要
職能培力學堂
計算機視覺與圖像分析
Computer Vision and Image Analysis
負責教師
陳永祥
學分
0.5
基本授課節數
9~10
1.應用經典圖像分析技術
2.使用OpenCV庫實現經典的圖像分析算法
3.比較經典和深度學習對象分類技術
4.使用Microsoft Cognitive Toolkit將Microsoft ResNet，一個深度卷積神經網絡（CNN）應用於對象分類
5.應用轉移學習來增強
1. Apply classical Image Analysis techniques, such as Edge Detection, Watershed and Distance Transformation as well as K-means Clustering to segment a basic dataset.
2. Implement classical Image Analysis algorithms using the OpenCV library.
3. Compare classical and Deep-Learning object classification techniques.
4. Apply Microsoft ResNet, a deep Convolutional Neural Network (CNN) to object classification using the Microsoft Cognitive Toolkit.
5.Apply Transfer Learning to augment ResNet18 for a Fully Convolutional Network (FCN) for Semantic Segmentation.