Students analyze images of Oscar Wilde used to publicize his 1882 American lecture tour. They then compare a caricature to another researched image, sharing this analysis in a podcast.
Students analyze World War II posters, as a group and then independently, to explore how argument, persuasion and propaganda differ.
Students will really warm up to this lesson about global warming as they study multimedia materials and use a variety of comprehension strategies.
Students will research how the development of the atomic bomb affected people in World War II, participate in a debate about the bomb's use, and investigate how it has affected people's lives since 1945.
ìExploring Imagery and Elevation Data in GIS Applicationsî (GEOG 480) focuses on the use of remotely sensed imagery and elevation data in GIS applications. Students enrolling in GEOG 480 should have a solid conceptual foundation in geospatial information science and technology. GEOG 480 is appropriate for those who are already working in the geospatial profession and wish to use imagery and elevation data in visualization and spatial analysis. Throughout the course, students confront realistic remote sensing problem scenarios that incorporate such skills and concepts as definition of data needs, metadata content standards, data formats and types, and analysis methods.
Students will learn the basic tools for analyzing images using description, reflection, and formal analysis.
Building on the strategies learned in the lesson 1, students will examine works of art in a museum setting.
Students will read an artist's statement by Dorothea Lange and write an artist's statement based on their own photographs.
This is an introductory course on computational thinking. We use the Julia programming language to approach real-world problems in varied areas, applying data analysis and computational and mathematical modeling. In this class you will learn computer science, software, algorithms, applications, and mathematics as an integrated whole. Topics include image analysis, particle dynamics and ray tracing, epidemic propagation, and climate modeling.
Machine Vision provides an intensive introduction to the process of generating a symbolic description of an environment from an image. Lectures describe the physics of image formation, motion vision, and recovering shapes from shading. Binary image processing and filtering are presented as preprocessing steps. Further topics include photogrammetry, object representation alignment, analog VLSI and computational vision. Applications to robotics and intelligent machine interaction are discussed.
Students will compare and contrast artworks depicting different viewpoints about war and will write captions that describe works of art in different media. They will also manipulate the image depicted in a photograph of a war in recent history.
Students analyze one of Dorothea Lange's photographs and make connections to its historical context by creating a one-page written and visual response.
The old cliche, "A picture is worth a thousand words" is put to the test when students write their own narrative interpretations of events shown in an image.
In this learning activity, students compare changes in insolation with changes in surface temperature in the polar regions using scientific visualizations of global data sets. Links to readings related to the shrinking ice cap and albedo are included. This is part 1 of a four-part activity on polar science. Extension activities examining air and sea surface temperature in relation to changing Earth albedo are included. This activity is one of several learning activities connected with the 2007 GLOBE Earth system poster.
Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others.
For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical foundations of the concept will be followed by a discussion of two or three relevant research papers in computer vision, medical and biological imaging, that use the concept in different ways. We will aim to understand the fundamental techniques and to recognize situations in which these techniques promise to improve the quality of the analysis.
This activity introduces students to what a digital image is and how it relates to the real world. It involves a simple training exercise on making linear and area measurements using NIH Image software. The activity is part of Exploring the Environment.
Verifying social media posts is quickly becoming a necessary endeavor in everyday life, let alone in the world of education. Social media has moved beyond a digital world which connects with friends and family and has become a quick and easy way to access news, information, and human interest stories from around the world. As this state of media has become the "new normal," especially for our younger generations, we, educators, find ourselves charged with a new task of teaching our students how to interact with and safely consume digital information.The following three modules are designed to be used as stand-alone activities or combined as one unit, in which the lessons can be taught in any order. "Who Said What?!" is a module focusing on author verification. "A Picture is Worth a Thousand Words'' is a module devoted to image verification. "Getting the Facts Straight" is a module designed to dive into information verification. Lastly, there are assessment suggestions to be utilized after completing all three modules.
Verifying social media posts is quickly becoming a necessary endeavor in everyday life, let alone in the world of education. Social media has moved beyond a digital world which connects with friends and family and has become a quick and easy way to access news, information, and human interest stories from around the world. As this state of media has become the "new normal," especially for our younger generations, we, educators, find ourselves charged with a new task of teaching our students how to interact with and safely consume digital information.The following three modules are designed to be used as stand-alone activities or combined as one unit, in which the lessons can be taught in any order. "Who Said What?!" is a module focusing on author verification. "A Picture is Worth a Thousand Words'' is a module devoted to image verification. "Getting the Facts Straight" is a module designed to dive into information verification. Lastly, there are assessment suggestions to be utilized after completing all three modules.