Paul Albert

2.8k citations
55 papers · 1.8k indexed · 1 hit paper · h-index 20

Paul Albert

53 papers receiving 1.7k citations

Hit Papers

Pseudo-labeling and confirmation bias in deep semi-superv...4182020202620222024100200300400

Peers

Paul Albert
Comparison fields: 5 of 160
  • Biochemistry 182
  • Insect Science 254
  • Computer Vision and Pattern Recognition 257
  • Artificial Intelligence 390
  • Nutrition and Dietetics 186
Replace Yi Lü with:
Yi Lü China
Seiya Imoto Japan
Guilherme P. Telles Brazil
Yixun Liu China
Rainer Schubert Germany
Alexandre Perera-Lluna Spain
Yuhang Zhang China
Simon Rogers United Kingdom
Philippe Besse France
Xue Jiang China
Paul Albert relative to Yi Lü China Yi Lü's profile →
Citations per field
00.5×8.3×
Yi Lü · 1×
Citations per year

Countries citing papers authored by Paul Albert

Since Specialization
Citations

This map shows the geographic impact of Paul Albert'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 Paul Albert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Albert more than expected).

Fields of papers citing papers by Paul Albert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Albert. 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 Paul Albert. The network helps show where Paul Albert may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Paul Albert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Paul Albert Line = papers co-authored together Paul Albert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20215
2
Semi-supervised dry herbage mass estimation using automatic data and\nsynthetic images
20214
3
Pseudo-labeling and confirmation bias in deep semi-supervised learningbreakdown →
2020418
4 20191
5 201413
6 201313
7 201363
8 201120
9 200943
10 200954
11 200959
12 200953
13 200940
14 200415
15 200431
16 200326
17 200230
18 199531
19 19885
20 198119

About Paul Albert

Paul Albert is a scholar working on Insect Science, Genetics, Immunology, Cellular and Molecular Neuroscience and Urology, having authored 55 papers that have together received 1.8k indexed citations. Recurring topics across this work include Insect Pheromone Research and Control (10 papers), Insect and Arachnid Ecology and Behavior (8 papers), Neurobiology and Insect Physiology Research (5 papers), Advanced Neural Network Applications (5 papers), Vitamin D Research Studies (4 papers), Forest Insect Ecology and Management (4 papers), Lepidoptera: Biology and Taxonomy (4 papers) and Machine Learning and Data Classification (4 papers). The work is most often cited by research in Biochemistry (182 citations), Insect Science (254 citations), Computer Vision and Pattern Recognition (257 citations), Artificial Intelligence (390 citations) and Nutrition and Dietetics (186 citations). Paul Albert has collaborated with scholars based in United States, Canada and Ireland. Frequent co-authors include Noel E. O’Connor, Kevin McGuinness, Eric Arazo, Diego Ortego, Amy D. Proal, Trevor G Marshall, W. D. Seabrook, Pirjo Pietinen, Mikko Virtanen and Phil R. Taylor. Their work appears in journals such as Annals of the New York Academy of Sciences, Journal of Chemical Ecology, Autoimmunity Reviews, Journal of Insect Physiology and Canadian Journal of Zoology.

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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