Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
VisualSEEk
19961.2k citationsJohn R. Smith, Shih‐Fu Changprofile →
Learning Locally-Adaptive Decision Functions for Person Verification
2013357 citationsLiangliang Cao, John R. Smith et al.profile →
Accelerating materials discovery using artificial intelligence, high performance computing and robotics
Citations per year, relative to John R. Smith John R. Smith (= 1×)
peers
Jing Liu
Countries citing papers authored by John R. Smith
Since
Specialization
Citations
This map shows the geographic impact of John R. 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 John R. Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John R. Smith more than expected).
This network shows the impact of papers produced by John R. 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 John R. Smith. The network helps show where John R. Smith may publish in the future.
Co-authorship network of co-authors of John R. Smith
This figure shows the co-authorship network connecting the top 25 collaborators of John R. Smith.
A scholar is included among the top collaborators of John R. 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 John R. Smith. John R. 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.
Merler, Michele, Dhiraj Joshi, Jinjun Xiong, et al.. (2018). The Excitement of Sports: Automatic Highlights Using Audio/Visual Cues.. Computer Vision and Pattern Recognition. 2520–2523.5 indexed citations
2.
Merler, Michele, et al.. (2017). Auto-Curation and Personalization of Sports Highlights Through Multimodal Excitement Measures. Computer Vision and Pattern Recognition. 1–9.1 indexed citations
3.
Smith, John R.. (2013). Herding Cats. IEEE Multimedia.4 indexed citations
4.
Cao, Liangliang, et al.. (2012). IBM T.J. Watson Research Center, Multimedia Analytics: Modality Classification and Case-Based Retrieval Tasks of ImageCLEF2012..2 indexed citations
5.
Cao, Liangliang, Shih-Fu Chang, Noel Codella, et al.. (2012). IBM Research and Columbia University TRECVID-2012 Multimedia Event Detection (MED), Multimedia Event Recounting (MER), and Semantic Indexing (SIN) Systems. TRECVID.11 indexed citations
6.
Cao, Liangliang, Shih‐Fu Chang, Noel Codella, et al.. (2011). IBM Research and Columbia University TRECVID-2011 Multimedia Event Detection (MED) System. TRECVID.21 indexed citations
7.
Natsev, Apostol, John R. Smith, Jelena Tešić, et al.. (2008). IBM Research TRECVID-2008 Video Retrieval System. TRECVID.19 indexed citations
8.
Campbell, Murray, et al.. (2006). IBM Research TRECVID-2006 Video Retrieval System. TRECVID.77 indexed citations
9.
Naphade, Milind, Apostol Natsev, Ching‐Yung Lin, & John R. Smith. (2004). MULTI-GRANULAR DETECTION OF REGIONAL SEMANTIC CONCEPTS. 109–112.3 indexed citations
Amir, Arnon, Giridharan Iyengar, Milind Naphade, et al.. (2003). IBM Research TRECVID 2004 Video Retrieval System.. TRECVID.91 indexed citations
12.
Rowe, Lawrence A., Harrick M. Vin, Thomas Plagemann, Prashant Shenoy, & John R. Smith. (2003). Proceedings of the eleventh ACM international conference on Multimedia.2 indexed citations
13.
Lin, Ching‐Yung, Belle L. Tseng, & John R. Smith. (2003). Video Collaborative Annotation Forum: Establishing Ground-Truth Labels on Large Multimedia Datasets. TRECVID.62 indexed citations
14.
Iyengar, Giridharan, C. Neti, Harriet J. Nock, et al.. (2002). IBM Research TREC 2002 Video Retrieval System.. Text REtrieval Conference.36 indexed citations
15.
Chang, Yuan‐Chi, Richard Han, Chung‐Sheng Li, & John R. Smith. (2002). Secure transcoding of internet content. 940–943.5 indexed citations
16.
Natsev, Apostol, Yuan‐Chi Chang, John R. Smith, Chung‐Sheng Li, & Jeffrey Scott Vitter. (2001). Supporting Incremental Join Queries on Ranked Inputs. Very Large Data Bases. 281–290.113 indexed citations
17.
Li, Chung‐Sheng, Yuan‐Chi Chang, Lawrence D. Bergman, & John R. Smith. (2000). Model-Based Multi-Modal Information Retrieval from Large Archives..2 indexed citations
18.
Smith, John R. & Shih‐Fu Chang. (1997). Querying by color regions using VisualSEEk content-based visual query system. 23–41.84 indexed citations
19.
Smith, John R. & Shih‐Fu Chang. (1997). Visual information retrieval from large distributed online. Communications of the ACM. 40(12). 63–71.1 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.