Name
Abstract | ||
|---|---|---|
Malaria prognosis, performed through the identification of parasites using microscopy, is a vital step in the early initiation of treatment. Malaria inducing parasites such as Plasmodium falciparum are difficult to identify and thus have a high mortality rate. For these reasons, a deep convolutional neural network algorithm is proposed in this paper to aid in accurately identifying parasitic cells... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/AIPR50011.2020.9425273 | 2020 IEEE Applied Imagery Pattern Recognition Workshop (AIPR) |
Keywords | DocType | ISSN |
Microscopy,Transfer learning,Cells (biology),Network architecture,Data models,National Institutes of Health,Complexity theory | Conference | 1550-5219 |
ISBN | Citations | PageRank |
978-1-7281-8243-8 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hussin K. Ragb | 1 | 0 | 0.34 |
| Ian T. Dover | 2 | 0 | 0.34 |
| Redha Ali | 3 | 0 | 0.34 |