Daniel Smith

1.5k total citations
59 papers, 1.1k citations indexed

About

Daniel Smith is a scholar working on Artificial Intelligence, Signal Processing and Genetics. According to data from OpenAlex, Daniel Smith has authored 59 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 13 papers in Signal Processing and 12 papers in Genetics. Recurrent topics in Daniel Smith's work include Genetic and phenotypic traits in livestock (11 papers), Animal Behavior and Welfare Studies (10 papers) and Speech and Audio Processing (8 papers). Daniel Smith is often cited by papers focused on Genetic and phenotypic traits in livestock (11 papers), Animal Behavior and Welfare Studies (10 papers) and Speech and Audio Processing (8 papers). Daniel Smith collaborates with scholars based in Australia, United States and Canada. Daniel Smith's co-authors include Greg Bishop-Hurley, James Hills, RP Rawnsley, D. Henry, Ashfaqur Rahman, Greg Timms, Ritaban Dutta, Simon Tabrett, Flora D. Salim and Aaron Ingham and has published in prestigious journals such as Biochemistry, Expert Systems with Applications and IEEE Access.

In The Last Decade

Daniel Smith

57 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel Smith Australia 17 316 220 218 197 159 59 1.1k
Philip Valencia Australia 14 145 0.5× 97 0.4× 111 0.5× 106 0.5× 109 0.7× 32 1.5k
Tim Wark Australia 26 236 0.7× 151 0.7× 133 0.6× 122 0.6× 178 1.1× 69 2.4k
Weizheng Shen China 21 287 0.9× 64 0.3× 226 1.0× 293 1.5× 64 0.4× 76 1.1k
Ritaban Dutta Australia 18 113 0.4× 68 0.3× 154 0.7× 131 0.7× 122 0.8× 62 1.4k
Dave L. Swain Australia 14 240 0.8× 125 0.6× 171 0.8× 159 0.8× 35 0.2× 34 969
Jaakko Mononen Finland 14 524 1.7× 234 1.1× 410 1.9× 104 0.5× 69 0.4× 65 1.1k
Craig Michie United Kingdom 22 238 0.8× 110 0.5× 219 1.0× 123 0.6× 63 0.4× 136 1.6k
Christos Tachtatzis United Kingdom 23 142 0.4× 61 0.3× 136 0.6× 89 0.5× 368 2.3× 96 1.8k
James Hills Australia 13 285 0.9× 205 0.9× 226 1.0× 172 0.9× 39 0.2× 31 678
C.P. Schofield United Kingdom 19 596 1.9× 178 0.8× 583 2.7× 134 0.7× 72 0.5× 44 1.5k

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-authorship network of co-authors of Daniel Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Smith. A scholar is included among the top collaborators of Daniel Smith 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 Daniel Smith. Daniel Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ahmedt‐Aristizabal, David, Daniel Smith, Xun Li, et al.. (2024). An In-Field Dynamic Vision-Based Analysis for Vineyard Yield Estimation. IEEE Access. 12. 102146–102166. 4 indexed citations
2.
Acharya, Debaditya, Vivien Rolland, Lars Petersson, et al.. (2024). Towards automatic anomaly detection in fisheries using electronic monitoring and automatic identification system. Fisheries Research. 272. 106939–106939. 7 indexed citations
3.
Xue, Hao, et al.. (2022). Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data. arXiv (Cornell University). 13 indexed citations
4.
McNally, Jody, Daniel Smith, Ashfaqur Rahman, et al.. (2019). Quantification of differences in resistance to gastrointestinal nematode infections in sheep using a multivariate blood parameter. Veterinary Parasitology. 270. 31–39. 9 indexed citations
5.
Shahin, Mostafa, Beena Ahmed, Daniel Smith, Andreas Duenser, & Julien Epps. (2019). Automatic Screening Of Children With Speech Sound Disorders Using Paralinguistic Features. 1–5. 7 indexed citations
6.
7.
Rahman, Ashfaqur, Andrew Hellicar, Daniel Smith, & John Henshall. (2015). Allele frequency calibration for SNP based genotyping of DNA pools: A regression based local–global error fusion method. Computers in Biology and Medicine. 61. 48–55. 3 indexed citations
8.
Hellicar, Andrew, Ashfaqur Rahman, Daniel Smith, & John Henshall. (2015). Machine learning approach for pooled DNA sample calibration. BMC Bioinformatics. 16(1). 214–214. 3 indexed citations
9.
Smith, Daniel, Ashfaqur Rahman, D. Henry, et al.. (2015). Heat event detection in dairy cows with collar sensors: An unsupervised machine learning approach. eCite Digital Repository (University of Tasmania). 1–4. 14 indexed citations
10.
Morello, Elisabetta B., Daniel Smith, Keith Ridgway, et al.. (2014). Quality Control (QC) procedures for Australia’s National Reference Station’s sensor data—Comparing semi-autonomous systems to an expert oceanographer. eCite Digital Repository (University of Tasmania). 9. 17–33. 16 indexed citations
11.
Smith, Daniel, et al.. (2014). Avoiding Marine Vehicles with Passive Acoustics. Journal of Field Robotics. 32(1). 152–166. 3 indexed citations
12.
Hellicar, Andrew, Daniel Smith, Ashfaqur Rahman, Ulrich Engelke, & John Henshall. (2014). A hierarchical learning approach to calibrate allele frequencies for SNP based genotyping of DNA pools. 7. 183–189. 3 indexed citations
13.
Duncan, Alec J., et al.. (2013). Modelling acoustic transmission loss due to sea ice cover. Acoustics Australia. 41(1). 79–87. 9 indexed citations
14.
Dutta, Ritaban, Daniel Smith, & Greg Timms. (2013). Dynamic annotation and visualisation of the South Esk hydrological sensor web. eCite Digital Repository (University of Tasmania). 105–110. 4 indexed citations
15.
Valin, Jean-Marc, et al.. (2008). An iterative linearised solution to the sinusoidal parameter estimation problem. Computers & Electrical Engineering. 36(4). 603–616. 1 indexed citations
16.
Smith, Daniel, et al.. (2005). A Sequential Approach to Sparse Component Analysis. 6. 1–4. 2 indexed citations
17.
Smith, Daniel, et al.. (2004). A two channel, block-adaptive audio separation technique based upon time-frequency information. UTS ePRESS (University of Technology Sydney). 393–396. 3 indexed citations
18.
Karlson-Stiber, Christine, Hans Persson, Andrew Heath, et al.. (1997). First clinical experiences with specific sheep Fab fragments in snake bite. Report of a multicentre study of Vipera berus envenoming. Journal of Internal Medicine. 241(1). 53–58. 58 indexed citations
19.
Malcolm, Bruce A., Christopher Lowe, Shirley Shechosky, et al.. (1995). Peptide Aldehyde Inhibitors of Hepatitis A Virus 3C Proteinase. Biochemistry. 34(25). 8172–8179. 52 indexed citations
20.
Robertson, Philip K., Matthew Hutchins, Duncan Stevenson, et al.. (1994). Mapping data into colour gamuts: Using interaction to increase usability and reduce complexity. Computers & Graphics. 18(5). 653–665. 5 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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