Name
Title | ||
|---|---|---|
Developed Newton-Raphson Based Deep Features Selection Framework for Skin Lesion Recognition |
Abstract | ||
|---|---|---|
•Artificial bee colony based contrast stretching is perform.•Lesion detection through faster RCNN along with pixels information.•Deep features are extracted using entropy based activation function.•A Newton Raphson based most discriminate features are selected. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.patrec.2019.11.034 | Pattern Recognition Letters |
Keywords | Field | DocType |
Skin cancer,Contrast stretching,Lesion localization,Deep features,Best features | Normalization (image processing),Computer vision,Feature selection,Pattern recognition,Convolutional neural network,Feature extraction,Artificial intelligence,Deep learning,Artificial neural network,Mathematics,Newton's method,Feed forward | Journal |
Volume | ISSN | Citations |
129 | 0167-8655 | 10 |
PageRank | References | Authors |
0.55 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Attique Khan | 1 | 69 | 11.89 |
| Muhammad Sharif | 2 | 317 | 37.96 |
| Tallha Akram | 3 | 53 | 7.27 |
| Syed Ahmad Chan Bukhari | 4 | 33 | 8.07 |
| Ramesh Sunder Nayak | 5 | 12 | 1.59 |