Demo Data from EDBT 2026 / reviewers in the wild / expert
Perry Lea
dblp:191/2437
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1
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.
| Computer networks
1 paper |
Wireless networking · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Embedded and real-time systems · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless networking › link adaptation
link rate adaptation |
0.8 | 1 | 2024 | ADR-X: ANN-Assisted Wireless Link Rate Adaptation for Compute-Constrained Embedded Gaming Devices · NSDI 2024 |
Methods — techniques the papers use, named apart from their topics
artificial neural network · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | ADR-X: ANN-Assisted Wireless Link Rate Adaptation for Compute-Constrained Embedded Gaming Devices
Murali Ramanujam, Joe Schaefer, Stan Adermann, Srihari Narlanka, Perry Lea, Ravi Netravali, Krishna Chintalapudi |
NSDI | 6 |
| 2016 | Signature line detection in scanned documentsabstractIn this paper, we present an algorithm to determine the signature line in scanned documents through a fast and computationally efficient technique. To that effect, the algorithm consists of three modules, namely pre-processing, candidate line detection and classification. Preprocessing in this case consists of hard thresholding, which is essential to line detection in the next module. The Hough transform for a single angle (horizontal) is utilized in the line detection module. Connected component analysis is utilized to merge detected Hough lines belonging to the same line on the document. Finally, the classification module attempts to classify each line as a signature line or not. This is accomplished using Histogram of a Gradient (HoG) features and a Euclidean distance measure for comparison. Prior data for this similarity comparison consists of images of target text in different font sizes and styles. The proposed algorithm showed favorable results in terms of precision and accuracy. Osborn de Lima, Shruty Janakiraman, Eli Saber, David C. Day, Peter Bauer, Mark Q. Shaw, Roger Twede, Perry Lea |
ICIP | 8 |