On the public citation graph

Wine Volume Estimation from Single-View Images as a Potential Tool in Dietary Monitoring Studies

https://doi.org/10.2139/ssrn.4017358
0 signed · 18 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.jacc.2017.06.054openalex-extracted
Relationship of Alcohol Consumption to All-Cause, Cardiovascular, and Cancer-Related Mortality in U.S. Adults
inferredcites →https://doi.org/10.1016/j.mam.2015.09.001openalex-extracted
Towards prevention and therapy of Alzheimer's disease
inferredcites →https://doi.org/10.1017/s0007114513002845openalex-extracted
Consumption of alcoholic beverages and cognitive decline at middle age: the Doetinchem Cohort Study
inferredcites →https://doi.org/10.1088/0957-0233/24/10/105701openalex-extracted
Model-based measurement of food portion size for image-based dietary assessment using 3D/2D registration
inferredcites →https://doi.org/10.1109/access.2020.2964386openalex-extracted
A Cloud-Based Framework for Machine Learning Workloads and Applications
inferredcites →https://doi.org/10.1109/cvpr.2017.195openalex-extracted
Xception: Deep Learning with Depthwise Separable Convolutions
inferredcites →https://doi.org/10.1109/icip.2016.7532312openalex-extracted
A comparison of food portion size estimation using geometric models and depth images
inferredcites →https://doi.org/10.1109/ism.2015.67openalex-extracted
Single-View Food Portion Estimation Based on Geometric Models
inferredcites →https://doi.org/10.21203/rs.3.rs-23998/v1openalex-extracted
inferredcites →https://doi.org/10.3390/molecules25215045openalex-extracted
Wine Intake in the Framework of a Mediterranean Diet and Chronic Non-Communicable Diseases: A Short Literature Review of the Last 5 Years
inferredcites →https://doi.org/10.3390/nu12103082openalex-extracted
Relationship between Wine Consumption, Diet and Microbiome Modulation in Alzheimer’s Disease
inferredcites →https://doi.org/10.48550/arxiv.1312.6034openalex-extracted
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-extracted
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1703.01365openalex-extracted
Axiomatic Attribution for Deep Networks
inferredcites →https://doi.org/10.48550/arxiv.1711.05101openalex-extracted
Decoupled Weight Decay Regularization
inferredcites →https://doi.org/10.5614/itbj.ict.res.appl.2014.8.1.1openalex-extracted
Volume Measurement Algorithm for Food Product with Irregular Shape using Computer Vision based on Monte Carlo Method
inferredcites →https://doi.org/10.1109/iccv.2017.207openalex-snapshot
See the Glass Half Full: Reasoning About Liquid Containers, Their Volume and Content
inferredcites →https://doi.org/10.3390/electronics10131556openalex-snapshot
Human-Mimetic Estimation of Food Volume from a Single-View RGB Image Using an AI System
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.