Remote Sensing Image Analysis and Interpretation: Classification with Bayes' theorem
Fourth lecture in the course 'Remote Sensing Image Analysis and Interpretation' covering the topics of Maximum likelihood estimation, maximum a posteriori estimation and how a classifier is evaluated.
slides: https://uni-bonn.sciebo.de/s/NS4RnVYJ7s68zyF
Lecturer: Ribana Roscher
Winter term 2020/2021, University of Bonn
Видео Remote Sensing Image Analysis and Interpretation: Classification with Bayes' theorem канала Ribana Roscher
slides: https://uni-bonn.sciebo.de/s/NS4RnVYJ7s68zyF
Lecturer: Ribana Roscher
Winter term 2020/2021, University of Bonn
Видео Remote Sensing Image Analysis and Interpretation: Classification with Bayes' theorem канала Ribana Roscher
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Remote Sensing Image Analysis and Interpretation: Image analysis and interpretation basics
Advanced Machine Learning for Remote Sensing: Train neural networks
Advanced Machine Learning for Remote Sensing: Welcome
Advanced Machine Learning for Remote Sensing: Neural Networks
Explain it to me - Facing Remote Sensing Challenges in the Bio- and Geosciences with Explainable ML
Advanced Machine Learning for Remote Sensing: Basics
What Identifies a Whale by its Fluke? On the Benefit of Interpretable ML for Whale Identification
Explainable machine learning (2022, 5th lecture): Interpret. by backward prop. + concept discovery
Explainable machine learning (2022, 4th lecture): Local model-agnostic methods
Learning with Real-World and Artificial Data for Improved Vehicle Detection in Aerial Imagery
Explainable machine learning (2022, 2nd lecture): Looking into a neural network
Explainable machine learning (2022, 1st lecture): Introduction
SemCity Toulouse: A Benchmark for Building Instance Segmentation in Satellite Images
Multi-Modal Deep Learning with Sentinel-3 Observations for the Detection of Oceanic Internal Waves
Advanced Machine Learning for Remote Sensing: Representation learning
Remote Sensing Image Analysis and Interpretation: Density estimation
Explainable machine learning (2022, 3rd lecture): Global model-agnostic methods
Remote Sensing Image Analysis and Interpretation: Introduction to Remote Sensing
Remote Sensing Image Analysis and Interpretation: Feature extraction and image segmentation
Advanced Machine Learning for Remote Sensing: Convolutional and Recurrent Neural Networks