Name
Abstract | ||
|---|---|---|
As smart mobile devices become pervasive, vendors are offering rich features supported by cloud-based servers to enhance the user experience. Such servers implement large-scale computing environments, where target data is compared to a massive preloaded database. CogniServe is a highly efficient recognition server for large-scale recognition that employs a heterogeneous architecture to provide low-power, high-throughput cores, along with application-specific accelerators. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/MM.2011.37 | IEEE Micro |
Keywords | Field | DocType |
large-scale computing environment,smart mobile device,large-scale recognition,heterogeneous architecture,efficient recognition server,massive preloaded database,cloud-based server,heterogeneous server architecture,application-specific accelerator,rich feature,high-throughput core,speech,user interfaces,speech recognition,hardware,computer architecture,cloud based computing,servers,programming,file servers,user experience,internet,image recognition | User experience design,Architecture,File server,Computer science,Server,Real-time computing,Mobile device,User interface,Operating system,The Internet,Distributed computing,Cloud computing | Journal |
Volume | Issue | ISSN |
31 | 3 | 0272-1732 |
Citations | PageRank | References |
12 | 0.76 | 0 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ravishankar K. Iyer | 1 | 1119 | 75.72 |
| Sadagopan Srinivasan | 2 | 120 | 7.87 |
| Omesh Tickoo | 3 | 389 | 31.58 |
| Zhen Fang | 4 | 91 | 7.62 |
| Rameshkumar Illikkal | 5 | 12 | 0.76 |
| Steven Zhang | 6 | 22 | 2.63 |
| Vineet Chadha | 7 | 195 | 17.02 |
| Paul Stillwell | 8 | 12 | 0.76 |
| Seung Eun Lee | 9 | 224 | 22.34 |