Name
Title | ||
|---|---|---|
A predictive function optimization algorithm for multi-spectral skin lesion assessment |
Abstract | ||
|---|---|---|
The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique used in the assessment of skin lesions. Unfortunately, this method is computationally expensive due to its function inverting process. In the work of this paper, we design a Predictive Function Optimization Algorithm in order to improve the efficiency of KMGA by speeding up its convergence rate. Using this approach, a High-Convergence-Rate KMGA (HCR-KMGA) is implemented onto multi-core processors and FPGA devices respectively. Furthermore, the implementations are optimized using parallel computing techniques. Intensive experiments demonstrate that HCR-KMGA can effectively accelerate KMGA method, while improving its assessment accuracy as well. |
Year | Venue | Keywords |
|---|---|---|
2015 | European Signal Processing Conference | Multi-spectral Image Processing,Light-Tissue Interaction,Genetic Algorithm,Kubelka-Munk model,Embedded System,SW/HW Co-design,FPGA,High-Level Synthesis,High-Performance Computing,POSIX Thread |
Field | DocType | ISSN |
Skin lesion,Computer science,Field-programmable gate array,Algorithm,Implementation,Function optimization,Rate of convergence,Multi spectral,Genetic algorithm,Signal processing algorithms | Conference | 2076-1465 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Li | 1 | 18 | 3.98 |
| Souleymane Balla-Arabe | 2 | 108 | 6.97 |
| Vincent Brost | 3 | 45 | 6.75 |
| Fan Yang | 4 | 11 | 5.91 |