Marco La Cascia
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 5%
- Human-Computer Interaction top 2%
- Signal Processing top 5%
- Media Technology top 2%
- Co-authors
- Stan SclaroffLiliana Lo PrestiVassilis AthitsosLeonid TaycherEdoardo ArdizzoneSunjay SethiSebastiano BattiatoAlessandro Capra
- Topics
- Advanced Image and Video Retrieval Techniques (31 papers)Image Retrieval and Classification Techniques (21 papers)Video Surveillance and Tracking Methods (16 papers)
- Partner nations
- ItalyUnited StatesSpain
In The Last Decade
Marco La Cascia
72 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 110
- Computer Vision and Pattern Recognition 1.7k
- Artificial Intelligence 305
- Human-Computer Interaction 214
- Signal Processing 201
- Media Technology 180
Countries citing papers authored by Marco La Cascia
This map shows the geographic impact of Marco La Cascia'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 Marco La Cascia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco La Cascia more than expected).
Fields of papers citing papers by Marco La Cascia
This network shows the impact of papers produced by Marco La Cascia. 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 Marco La Cascia. The network helps show where Marco La Cascia may publish in the future.
Co-authorship network of co-authors of Marco La Cascia
This figure shows the co-authorship network connecting the top 25 collaborators of Marco La Cascia. A scholar is included among the top collaborators of Marco La Cascia 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 Marco La Cascia. Marco La Cascia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 22 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 29 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | User detection through multi-sensor fusion in an AmI scenario | 14 |
| 10 | 9 | |
| 11 | 5 | |
| 12 | 7 | |
| 13 | 7 | |
| 14 | 8 | |
| 15 | 1 | |
| 16 | 43 | |
| 17 | 40 | |
| 18 | 28 | |
| 19 | 388 | |
| 20 | 17 |
About Marco La Cascia
Marco La Cascia is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Media Technology, having authored 76 papers that have together received 2.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (31 papers), Image Retrieval and Classification Techniques (21 papers) and Video Surveillance and Tracking Methods (16 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.7k citations), Human-Computer Interaction (214 citations) and Media Technology (180 citations). Marco La Cascia has collaborated with scholars based in Italy, United States and Spain. Frequent co-authors include Stan Sclaroff, Liliana Lo Presti, Vassilis Athitsos, Leonid Taycher, Edoardo Ardizzone, Sunjay Sethi, Sebastiano Battiato, Alessandro Capra, Ilenia Tinnirello and Marco Morana. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.
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.