Evidence map›Paper›PMID 30393785›Full record

ArticleIPSN : [proceedings]. IPSN (Conference)2017

Poster Abstract: 3D Activity Localization With Multiple Sensors.

Xinyu Li, Yanyi Zhang, Jianyu Zhang, Shuhong Chen, Yue Gu, Richard A Farneth, Ivan Marsic, Randall S Burd

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IPSN : [proceedings]. IPSN (Conference), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xinyu LiRutgers University, Piscataway, New Jersey.
Yanyi ZhangRutgers University, Piscataway, New Jersey.
Jianyu ZhangRutgers University, Piscataway, New Jersey.
Shuhong ChenRutgers University, Piscataway, New Jersey.
Yue GuRutgers University, Piscataway, New Jersey.
Richard A FarnethChildren's National Medical Center, Washington, District of Columbia.
Ivan MarsicRutgers University, Piscataway, New Jersey.
Randall S BurdChildren's National Medical Center, Washington, District of Columbia.

Funding

Intention-aware Recommender System for Improving Trauma Resuscitation OutcomesR01LM011834 · NLM · CHILDREN'S RESEARCH INSTITUTE · PI BURD, RANDALL S., MARSIC, IVAN · 2014 to 2023
$4.7M
NLM NIH HHS R01 LM011834
6 · The paper itself

Abstract

We present a deep learning framework for fast 3D activity localization and tracking in a dynamic and crowded real world setting. Our training approach reverses the traditional activity localization approach, which first estimates the possible location of activities and then predicts their occurrence. Instead, we first trained a deep convolutional neural network for activity recognition using depth video and RFID data as input, and then used the activation maps of the network to locate the recognized activity in the 3D space. Our system achieved around 20cm average localization error (in a 4

Indexed as

Activity RecognitionActivity recognition and understandingActivity TrackingComputer systems organizationComputing methodologiesDeep LearningLocolizationPassive RFIDReal-time system architecture

Identifiers

PMID30393785
PMCPMC6214452

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.