Daniel Smith

57 papers receiving 1.0k citations

Peers

Daniel Smith
Comparison fields: 5 of 120
  • Small Animals 316
  • Animal Science and Zoology 218
  • Developmental Biology 29
  • Food Science 197
  • Signal Processing 115
Replace Dave L. Swain with:
Dave L. Swain Australia
Jaakko Mononen Finland
Tim Wark Australia
Mark Trotter Australia
Weizheng Shen China
James Hills Australia
Tilo Burghardt United Kingdom
Greg Bishop-Hurley Australia
Philip Valencia Australia
Dongjian He China
Daniel Smith relative to Dave L. Swain Australia Dave L. Swain's profile →
Citations per field
00.5×5.5×
Dave L. Swain · 1×
Citations per year

Countries citing papers authored by Daniel Smith

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Smith, 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 Daniel Smith Line = papers co-authored together Daniel Smith links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014147
2 2016102
3 201677
4 199758
5 201755
6 201354
7 199552
8 202250
9 201428
10 201625
11 202025
12 201224
13 202123
14 201423
15 202022
16 201120
17 201320
18 201416
19 201415
20 202015

About Daniel Smith

Daniel Smith is a scholar working on Small Animals, Signal Processing, Animal Science and Zoology, Equine and Geology, having authored 59 papers that have together received 1.1k indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (11 papers), Animal Behavior and Welfare Studies (10 papers), Speech and Audio Processing (8 papers), Effects of Environmental Stressors on Livestock (7 papers), Blind Source Separation Techniques (7 papers), Water Quality Monitoring Technologies (6 papers), Food Supply Chain Traceability (4 papers) and Advanced Adaptive Filtering Techniques (4 papers). The work is most often cited by research in Small Animals (316 citations), Animal Science and Zoology (218 citations), Developmental Biology (29 citations), Food Science (197 citations) and Signal Processing (115 citations). Daniel Smith has collaborated with scholars based in Australia, United States and Canada. Frequent co-authors include Greg Bishop-Hurley, James Hills, RP Rawnsley, Ashfaqur Rahman, D. Henry, Greg Timms, Ritaban Dutta, Simon Tabrett, Flora D. Salim and Paulo de Souza. Their work appears in journals such as Computers and Electronics in Agriculture, IEEE Sensors Journal, Sensors, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies and Knowledge-Based Systems.

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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