G.G. Walter
- Computer Vision and Pattern Recognition top 2%
- Applied Mathematics top 2%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Signal Processing top 5%
- Topics
- Image and Signal Denoising Methods (15 papers)Mathematical Analysis and Transform Methods (15 papers)Advanced Statistical Methods and Models (5 papers)
- Journals
- IEEE Transactions on Information TheoryIEEE Transactions on Signal ProcessingPattern Recognition
- Partner nations
- United StatesAustriaFinland
In The Last Decade
G.G. Walter
40 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 486
- Applied Mathematics 382
- Artificial Intelligence 338
- Control and Systems Engineering 321
- Signal Processing 193
Countries citing papers authored by G.G. Walter
This map shows the geographic impact of G.G. Walter'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 G.G. Walter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G.G. Walter more than expected).
Fields of papers citing papers by G.G. Walter
This network shows the impact of papers produced by G.G. Walter. 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 G.G. Walter. The network helps show where G.G. Walter may publish in the future.
Co-authorship network of co-authors of G.G. Walter
This figure shows the co-authorship network connecting the top 25 collaborators of G.G. Walter. A scholar is included among the top collaborators of G.G. Walter 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 G.G. Walter. G.G. Walter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | ANNUAL INDICES OF SKIPJACK TUNA (KATSUWONUS PELAMIS) LARVAE IN THE GULF OF MEXICO (1982-2011) | 1 |
| 2 | DEVELOPMENT OF INDICES OF LARVAL BLUEFIN TUNA (THUNNUS THYNNUS) IN THE WESTERN MEDITERRANEAN SEA | 9 |
| 3 | 6 | |
| 4 | ANNUAL INDICES OF BLUEFIN TUNA (THUNNUS THYNNUS) SPAWNING BIOMASS IN THE GULF OF MEXICO DEVELOPED USING DELTA-LOGNORMAL AND MULTIVARIATE MODELS | 3 |
| 5 | 1 | |
| 6 | 42 | |
| 7 | 1 | |
| 8 | 37 | |
| 9 | 24 | |
| 10 | 52 | |
| 11 | Wavelet neural networks for function learningbreakdown → | 539 |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 8 | |
| 17 | 6 | |
| 18 | 99 | |
| 19 | 2 | |
| 20 | 7 |
About G.G. Walter
G.G. Walter is a scholar working on Applied Mathematics, Statistics and Probability and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 1.3k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (15 papers), Mathematical Analysis and Transform Methods (15 papers) and Advanced Statistical Methods and Models (5 papers). The work is most often cited by research in Applied Mathematics (382 citations), Computer Vision and Pattern Recognition (486 citations) and Signal Processing (193 citations). G.G. Walter has collaborated with scholars based in United States, Austria and Finland. Frequent co-authors include Jun Zhang, J. R. Blum, G. G. Hamedani, V. Susarla, Jie Zhang, Hamid Krim, Xiaoping Shen, N. J. Salamon, Ahmed I. Zayed and Alireza Baghai‐Wadji. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and Pattern Recognition.
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.