MLRCV: Introduction (Summer 2021)
Introduction lecture for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
MLRCV: Regression (Summer 2021)
Regression lecture for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
00:00 Introduction & Recap
00:54 Linear Regression
03:22 Notation
04:55 Probabilistic Parameter Model
06:07 Types of Parameter Estimation Methods
07:10 Maximum Likelihood Estimation (MLE) for Linear Regression
18:27 MLE for Non-linear Functions
21:37 Overfitting with MLE
24:22 Maximum A Posteriori Estimation (MAP) for Linear Regression
28:35 Bayesian Linear Regression
51:48 Discriminative vs. Generative Models
MLRCV: Classification (Summer 2021)
Classification lecture for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
00:00 Introduction
03:38 Naive Bayes
15:40 Decision Tree
31:10 Logistic Regression
51:10 Softmax Regression
MLRCV: Ensemble learning (Summer 2021)
Ensemble models lecture for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
00:00 Introduction
03:40 Bagging
08:25 Random Forest
22:45 AdaBoost
46:00 Gradient Boosting
MLRCV: Unsupervised learning (Summer 2021)
Unsupervised learning lecture for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
00:00 Introduction
01:53 Gaussian Mixture Model
31:10 Principal Component Analysis
45:30 t-Stochastic Neighbor Embedding
MLRCV: ML for Computer Vision Tasks (Summer 2021)
Traditional ML-based methods for computer vision tasks for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
00:00 Introduction
03:30 Perception Tasks
08:00 General Object Detector
16:20 Viola Jones Object Face Detection
26:25 Histogram of Oriented Gradients (HOG)
31:00 Datasets & Benchmarks: Pascal VOC
35:00 Deformable Part Models (DPM)
38:00 Selective Search
49:20 Image Classification & ImageNet
MLRCV: Introduction to CNNs (Summer 2021)
Introduction to Convolutional Neural Network (CNN) for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
00:00 Introduction
10:30 Neural Networks
23:00 Convolutional Neural Networks
44:45 AlexNet
MLRCV: Learning CNNs (Summer 2021)
Learning CNNs for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer term of 2021.
00:00 Introduction
02:20 Losses
08:30 Backpropagation
35:40 Optimization Methods
51:00 Weight Initialization
58:20 Normalization of Layers
MLRCV: Building CNNs (Summer 2021)
Building CNNs for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer of 2021.
00:00 Introduction
02:10 AlexNet
03:40 ZFNet
04:15 VGG Net
07:45 GoogleLeNet
12:30 ResNet
20:50 MobileNet
25:40 MobileNetV2
29:30 Neural Architecture Search (NAS)
34:30 EfficientNet
41:00 Current CNN Trends & Architecture choice
45:30 Overfitting & Generalization
47:00 Network-based adaptations (L2-regularization, Dropout, Stochastic Depth)
51:00 Data-based adaptions (RandAugment, mixup, cutout, cutmix)
MLRCV: Object Detection with CNNs (Summer 2021)
Object Detection with CNNs for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer of 2021.
MLRCV: Segmentation with CNNs (Summer 2021)
Segmentation with CNNs for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer of 2021.
MLRCV: Beyond Supervised Learning (Summer 2021)
Beyond supervised learning for the course “Machine Learning for Robotics and Computer Vision” (MLRCV) taught at the University of Bonn in the summer of 2021.