Resizing

Human Vision

Color Spaces

Transforms

Image Coordinates

Filters

Convolution

Edges and Features

Harris Corner Detector

Feature Matching

RANSAC (Random Sample Consensus)

HOG (Histogram of Oriented Gradients)

SIFT (Scale-invariant Feature Transform)

Optical Flow

Depth Perception

Stereo

Neural network

Convolutional neural network (CNN)

Network Architectures

Semantic Segmentation

Object Detection

Instance Segmentation

Vision and Language

Generative adversarial network (GAN)

CSE 455 Computer Vision University of Washington Winter 2022 A general introduction to computer vision, this course covers traditional image processing techniques and newer, machine-learning based approaches. It discusses topics like filtering, edge detection, stereo, flow, and neural network architectures. This class is a general introduction to computer vision. It covers standard techniques in image processing like filtering, edge detection, stereo, flow, etc. (old-school vision), as well as newer, machine-learning based computer vision.   

CSE 455 Computer Vision

Computer Vision

Stack (abstract data type)

Linked list

Interface

Encapsulation

List (abstract data type)

Abstract Data Type (ADT)

`ArrayIntList`

pre/post conditions

Exception handling

Reference Semantics

Queue (abstract data type)

List Nodes

`LinkedIntList`

Recursion (computer science)

Recursive Tracing

Set (abstract data type)

Map (higher-order function)

Grammars

Binary Search

Recursive Backtracking

Binary tree

Binary Search Tree (BST)

Comparable

Generics

Priority Queues

Huffman

Inheritance (object-oriented programming)

Hashing

Sorting algorithm

Iterators

Abstract Classes

Computational complexity

CSE 143 Computer Programming II University of Washington Summer 2022 This course is a continuation of CSE 142, focusing on manipulating data, implementing data structures, and learning about algorithms in Java. It delves into abstract data types, recursion, inheritance, and more.  This course is a continuation of CSE 142. While CSE 142 focused on topics of program control (loops, conditionals, methods, parameter passing, etc.), CSE 143 focuses on topics ofb manipulating data. Topics include: abstract data types (ADTs), lists, stacks, queues, linked lists, binary trees, recursion, interfaces, inheritance, and encapsulation. Students will also learn about the notion of complexity and how to evaluate performance trade-offs of classic algorithms (such as sorting and searching) and classic data structures (such as lists, sets, and maps). The course will include a mixture of implementing data structures and using components from the Java Collections Framework.  ## Textbook

Our optional textbook for CSE 143 this quarter will be the following:

Reges/Stepp. Building Java Programs: A Back to Basics Approach, 5th edition. ISBN 978-0135471944

- [Building Java Programs: A Back to Basics Approach (authors' web site)](http://www.buildingjavaprograms.com/)

This book was written specifically for this course and makes a valuable supplement to the lecture presentations.

## Code Files

The textbook includes many sample programs. You can access a full set of [code files](http://www.buildingjavaprograms.com/code_files/) that is organized chapter by chapter. This will allow you to download any of the programs and run them on your own computer.

## Video Notes

New copies of the textbook come with an access code to watch "Video Notes." These videos supplement the lecture and book material by walking through more examples in detail. You can access the video notes at the Pearson [VideoNotes](http://www.pearsonhighered.com/regesstepp/) web site.

CSE 143 Computer Programming II

Computer Programming

Resizing

2 courses cover this concept

CSE 455 Computer Vision

CSE 143 Computer Programming II