ArticleSensors (Basel, Switzerland)2020
An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- New interactive machine learning tool for marine image analysis.Royal Society open science · 2024Article
- Image dataset for benchmarking automated fish detection and classification algorithms.Scientific data · 2023Article
- A data science approach for multi-sensor marine observatory data monitoring cold water corals (Paragorgia arborea) in two campaigns.PloS one · 2023Article
- Phenology in the deep sea: seasonal and tidal feeding rhythms in a keystone octocoral.Proceedings. Biological sciences · 2022Article
- A low-cost, long-term underwater camera trap network coupled with deep residual learning image analysis.PloS one · 2022Article
- Autonomous Surface and Underwater Vehicles as Effective Ecosystem Monitoring and Research Platforms in the Arctic-The Glider Project.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Imaging technologies are being deployed on cabled observatory networks worldwide. They allow for the monitoring of the biological activity of deep-sea organisms on temporal scales that were never attained before. In this paper, we customized Convolutional Neural Network image processing to track behavioral activities in an iconic conservation deep-sea species-the bubblegum coral
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What OpenQuestion holds
Registered trials
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.