Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Susan M. Haynes

dblp:166/9996 · also Susan Makrouhee Haynes · DBLP profile ↗
← Back
4ranked-venue papers
4as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 3 · 3 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
3D vision · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › motion estimation
motion correspondence
0.011991
Trajectories and events · CVPR 1991

Methods — techniques the papers use, named apart from their topics

line fitting · 0.0constraint satisfaction · 0.0
YearPublicationVenuePosition
2013 Using the atmel AVR (arduino microcontroller) as the foundation of beginning computer organization course (abstract only)
abstract
This poster describes our experiences, materials and plans using the Atmel AVR, a RISC microprocessor, for teaching beginning computer organization at the college level. In particular, we use this microprocessor, typically packaged into the Arduino, to give hands-on experience with: (1) Assembly language programming, including ISA (16 bit instructions), multiple types of branches, multiple addressing modes, (2) C language programming, (3) interrupt programming, (4) I/O programming, and (5) programming on-board components, e.g., timers/counters.
Susan M. Haynes
SIGCSE1
1991 Trajectories and events
abstract
A solution to the correspondence problem using constraint satisfaction is described. It uses a real-time line-fitting algorithm to detect changes in a point's motion parameters as they happen. A trajectory is hypothesized for a single point's motion. Since the event detected may be wrong, multiple trajectories are hypothesized for each point. A correspondence is drawn from the set of hypothesized trajectories. The algorithm is robust, working on noisy and non-rigid motion data, and does not use false precision.>
Susan M. Haynes, Ramesh Jain 0001
CVPR1
1983 Detection of moving edges
Susan M. Haynes, Ramesh Jain 0001
Comput. Vis. Graph. Image Process.1
1982 Detection of moving edges
Susan M. Haynes, Ramesh Jain 0001
Comput. Graph. Image Process.1