Daniel Heesch

511 citations
17 papers · 198 indexed · h-index 8

Daniel Heesch

17 papers receiving 179 citations

Peers

Daniel Heesch
Comparison fields: 5 of 48
  • Computer Vision and Pattern Recognition 162
  • Signal Processing 20
  • Media Technology 13
  • Human-Computer Interaction 7
  • Artificial Intelligence 25
Replace Yin-Hsi Kuo with:
Yin-Hsi Kuo Taiwan
Georg Thallinger Austria
Paolo Bolettieri Italy
Michael D. Garris United States
Christine J. Sandom United Kingdom
Wojciech Basalaj United Kingdom
Kaiser J. Giri India
Shant Navasardyan United States
Balázs Kovács United States
Paulo Villegas Spain
Daniel Heesch relative to Yin-Hsi Kuo Taiwan Yin-Hsi Kuo's profile →
Citations per field
00.5×1.5×
Yin-Hsi Kuo · 1×
Citations per year

Countries citing papers authored by Daniel Heesch

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Heesch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 10 scholars most cited alongside Daniel Heesch, 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 Heesch Line = papers co-authored together Daniel Heesch links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 20095
2 200911
3 200871
4 20076
5 20076
6 20069
7 20053
8
Do "Attractive Things Work Better"? An Exploration of Search Tool Visualisations
200511
9
Visual Features for Content-based Medical Image Retrieval.
20044
10
Video Retrieval Using Search and Browsing.
200419
11 20043
12 20041
13 20047
14
NN Networks for Content-Based Image Retrieval
20043
15
Video Retrieval Using Search and Browsing with Key Frames.
20034
16
Info Navigator: A visualization tool for document searching and browsing
200318
17
Video Retrieval Using Global Features in Keyframes.
200217

About Daniel Heesch

Daniel Heesch is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Media Technology, Signal Processing and Literature and Literary Theory, having authored 17 papers that have together received 198 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (13 papers), Image Retrieval and Classification Techniques (12 papers), Video Analysis and Summarization (8 papers), Advanced Vision and Imaging (3 papers), Music and Audio Processing (1 paper), Plant and animal studies (1 paper), Digital Humanities and Scholarship (1 paper) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (162 citations), Signal Processing (20 citations), Media Technology (13 citations), Human-Computer Interaction (7 citations) and Artificial Intelligence (25 citations). Daniel Heesch has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Stefan Rüger, Maria Petrou, Peter Howarth, David Bull, João Magalhães, R.J. O'Callaghan, M. Petrou, Alexander May, Brock Craft and Paul Cairns. Their work appears in journals such as Theoretical Population Biology, Multimedia Tools and Applications, Journal of Signal Processing Systems, Text REtrieval Conference and TRECVID.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026