EDBT 2026 Demo / reviewers in the wild / expert
Siyan Zhou
dblp:227/5478
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0002-8840-5066ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-authorArtificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 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.
| Artificial intelligence
1 paper |
Segmentation and scene understanding · 77% Efficient and distributed learning · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Segmentation and scene understanding › biomedical image segmentation
connectomics segmentation |
0.4 | 1 | 2020 | Two Stream Active Query Suggestion for Active Learning in Connectomics · ECCV (18) 2020 |
Machine learning › Efficient and distributed learning
active learning |
0.1 | 1 | 2020 | Two Stream Active Query Suggestion for Active Learning in Connectomics · ECCV (18) 2020 |
Methods — techniques the papers use, named apart from their topics
two-stream network · 0.4active learning · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Two Stream Active Query Suggestion for Active Learning in Connectomics
Zudi Lin, Donglai Wei 0001, Won-Dong Jang, Siyan Zhou, Xupeng Chen, Xueying Wang 0002, Richard Schalek, Daniel R. Berger, Brian Matejek, Lee Kamentsky, Adi Suissa, Daniel Haehn, Thouis R. Jones, Toufiq Parag, Jeff Lichtman, Hanspeter Pfister |
ECCV (18) | 4 |
| 2020 | Rate-distortion model for grayscale-invariance reversible data hiding
Siyan Zhou, Weiming Zhang 0001, Chaomin Shen 0001 |
Signal Process. | 1 |
| 2018 | Design and Evaluation of a Multimodal Science SimulationabstractWe present a multimodal science simulation, including visual and auditory (descriptions, sound effects, and sonifications) display. The design of each modality is described, as well as evaluation with learners with and without visual impairments. We conclude with challenges and opportunities at the intersection of multiple modalities. Brianna J. Tomlinson, Prakriti Kaini, Siyan Zhou, Taliesin L. Smith, Emily B. Moore, Bruce N. Walker |
ASSETS | 3 |