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researcher

David S. Rosenblum

Constructor University

13 papers hereh-index 5012.6k citations215 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5
  • last author6

Across the 11 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG2
  • cs.SE2
  • cs.AI1
  • cs.CY1
  • cs.FL1
affiliations
  • Constructor University
Homepage
same name
  • David S. Rosenblum — 1 paper
  • David S. Rosenblum — 1 paper, h 4
  • David S. Rosenblum — 1 paper, h 3
  • David S. Rosenblum — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132021
most citedAction2Activity: Recognizing Complex Activities from Sensor Data

297 citations · 545 across the 13 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2020★ 7 cited

Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics

Yuxuan Liang, Kun Ouyang, Yiwei Wang +4

Citywide crowd flow analytics is of great importance to smart city efforts. It aims to model the crowd flow (e.g., inflow and outflow) of each region in a city based on historical…

cs.CV2020★ 2 cited

Fine-Grained Urban Flow Inference

Kun Ouyang, Yuxuan Liang, Ye Liu +4

The ubiquitous deployment of monitoring devices in urban flow monitoring systems induces a significant cost for maintenance and operation. A technique is required to reduce the num…

cs.CV2019★ 126 cited

UrbanFM: Inferring Fine-Grained Urban Flows

Yuxuan Liang, Kun Ouyang, Lin Jing +5

Urban flow monitoring systems play important roles in smart city efforts around the world. However, the ubiquitous deployment of monitoring devices, such as CCTVs, induces a long-l…

cs.CV2016★ 297 cited

Action2Activity: Recognizing Complex Activities from Sensor Data

Ye Liu, Liqiang Nie, Lei Han +2

As compared to simple actions, activities are much more complex, but semantically consistent with a human's real life. Techniques for action recognition from sensor generated data…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.