Adrian Johnston

434 total citations · 1 hit paper
6 papers, 250 citations indexed

About

Adrian Johnston is a scholar working on Computer Vision and Pattern Recognition, Pediatrics, Perinatology and Child Health and Computational Mechanics. According to data from OpenAlex, Adrian Johnston has authored 6 papers receiving a total of 250 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 2 papers in Pediatrics, Perinatology and Child Health and 2 papers in Computational Mechanics. Recurrent topics in Adrian Johnston's work include Advanced Vision and Imaging (3 papers), Prenatal Screening and Diagnostics (2 papers) and Reproductive Biology and Fertility (2 papers). Adrian Johnston is often cited by papers focused on Advanced Vision and Imaging (3 papers), Prenatal Screening and Diagnostics (2 papers) and Reproductive Biology and Fertility (2 papers). Adrian Johnston collaborates with scholars based in Australia and United States. Adrian Johnston's co-authors include Jonathan M. M. Hall, Sonya M. Diakiw, Michelle Perugini, Don Perugini, Matthew VerMilyea, Andrew Miller, A. Picou, Ravi Garg, Ian Reid and Anton van den Hengel and has published in prestigious journals such as Human Reproduction, Reproductive BioMedicine Online and Adelaide Research & Scholarship (AR&S) (University of Adelaide).

In The Last Decade

Adrian Johnston

5 papers receiving 233 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF

2020 186 citations Matthew VerMilyea, Jonathan M. M. Hall et al. Human Reproduction profile →

Peers

Adrian Johnston

PHEOH

PPCH

RM

MB

HI

Marco Toschi United States

Rohan Pooniwala United States

Adolfo Flores-Saiffe Farías Mexico

Tracey Griffiths United Kingdom

Leslie B. Ramirez United States

Lynn M. Boehnlein United States

Pantelis Zisimopoulos Israel

Jonas Malmsten United States

Ashleigh Storr Australia

Marco Toschi United States

Adrian Johnston

226 ×1.4

PHEOH

136 ×1.3

PPCH

169 ×2.0

RM

63 ×2.0

MB

36 ×1.2

HI

Citations per year, relative to Adrian Johnston Adrian Johnston (= 1×) peers Marco Toschi

Countries citing papers authored by Adrian Johnston

Since Specialization

Citations

This map shows the geographic impact of Adrian Johnston's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Adrian Johnston with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrian Johnston more than expected).

Fields of papers citing papers by Adrian Johnston

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Adrian Johnston. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Adrian Johnston. The network helps show where Adrian Johnston may publish in the future.

Co-authorship network of co-authors of Adrian Johnston

This figure shows the co-authorship network connecting the top 25 collaborators of Adrian Johnston. A scholar is included among the top collaborators of Adrian Johnston based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Adrian Johnston. Adrian Johnston is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Diakiw, Sonya M., Jonathan M. M. Hall, Matthew VerMilyea, et al.. (2022). An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos. Reproductive BioMedicine Online. 45(6). 1105–1117. 39 indexed citations

2.

VerMilyea, Matthew, Jonathan M. M. Hall, Sonya M. Diakiw, et al.. (2020). Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF. Human Reproduction. 35(4). 770–784. 186 indexed citations breakdown →

3.

Johnston, Adrian & Gustavo Carneiro. (2019). Single View 3D Point Cloud Reconstruction using Novel View Synthesis and Self-Supervised Depth Estimation. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 1–8.

4.

Johnston, Adrian, Ravi Garg, Gustavo Carneiro, Ian Reid, & Anton van den Hengel. (2017). Scaling CNNs for High Resolution Volumetric Reconstruction from a Single Image. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 2. 930–939. 20 indexed citations

5.

Johnston, Adrian, et al.. (2015). 3-D Modeling from Concept Sketches of Human Characters with Minimal User Interaction. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 1. 1–8. 1 indexed citations

6.

Falkner, Katrina, Vanea Chiprianov, Nickolas Falkner, et al.. (2013). Model-Driven Performance Prediction of Distributed Real-Time Embedded Defense Systems. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 73. 155–158. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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