Michael Lam
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- Advanced Image and Video Retrieval Techniques 2
- Visual Attention and Saliency Detection 1
- Signal Processing top 5%
- Music and Audio Processing 1
- Artificial Intelligence top 10%
- AI in cancer detection 1
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- Visual and Cognitive Learning Processes 1
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- Marine Invertebrate Physiology and Ecology 1
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- Coral and Marine Ecosystems Studies 1
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- Lung Cancer Diagnosis and Treatment 1
- Co-authors
- Siniša TodorovićBehrooz MahasseniJacob FurstDaniela RaicuThomas G. DietterichJanardhan Rao DoppaDavid MazurskyZachary Estes
- Journals
- Journal of Cognitive Psychology (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)
- Partner nations
- United StatesSwitzerlandItaly
In The Last Decade
Michael Lam
6 papers receiving 499 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 469
- Signal Processing 233
- Artificial Intelligence 105
- Developmental Biology 6
- Sociology and Political Science 72
Countries citing papers authored by Michael Lam
This map shows the geographic impact of Michael Lam'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 Michael Lam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Lam more than expected).
Fields of papers citing papers by Michael Lam
This network shows the impact of papers produced by Michael Lam. 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 Michael Lam. The network helps show where Michael Lam may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Michael Lam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Unsupervised Video Summarization with Adversarial LSTM Networksbreakdown → | 2017 | 366 |
| 2 | 2017 | 88 | |
| 3 | 2016 | 10 | |
| 4 | 2015 | 13 | |
| 5 | 2013 | 7 | |
| 6 | 2007 | 35 |
About Michael Lam
Michael Lam is a scholar working on Computer Vision and Pattern Recognition, Paleontology, Artificial Intelligence, Signal Processing and Nature and Landscape Conservation, having authored 6 papers that have together received 519 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), Visual and Cognitive Learning Processes (1 paper), Marine Invertebrate Physiology and Ecology (1 paper), Visual Attention and Saliency Detection (1 paper), Music and Audio Processing (1 paper), Coral and Marine Ecosystems Studies (1 paper), Lung Cancer Diagnosis and Treatment (1 paper) and AI in cancer detection (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (469 citations), Signal Processing (233 citations), Artificial Intelligence (105 citations), Developmental Biology (6 citations) and Sociology and Political Science (72 citations). Michael Lam has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Siniša Todorović, Behrooz Mahasseni, Jacob Furst, Daniela Raicu, Thomas G. Dietterich, Janardhan Rao Doppa, David Mazursky, Zachary Estes, Michael Gibbert and Abigail Reft. Their work appears in journals such as Journal of Cognitive Psychology and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.