| dc.contributor.author | Wasi, Sefatul | |
| dc.contributor.author | Alam, Saadia Binte | |
| dc.contributor.author | Rahman, Rashedur | |
| dc.contributor.author | Amin, M Ashraful | |
| dc.contributor.author | Kobashi, Syoji | |
| dc.date.accessioned | 2023-10-09T10:22:36Z | |
| dc.date.available | 2023-10-09T10:22:36Z | |
| dc.date.issued | 2023-10 | |
| dc.identifier.uri | https://ar.iub.edu.bd/handle/123456789/573 | |
| dc.description.abstract | Kidney tumor is a health concern that affects kidney cells and may leads to mortality depending on their type. Benign tumors can be unproblematic whereas malignant tumors pose the threat of kidney cancer. Early detection and diagnosis are possible through kidney tumor recognition based on deep learning techniques. In this paper, a method based on transfer learning using deep convolutional neural network (DCNN) is proposed to recognize kidney tumor from computed tomography (CT) images. The proposed method was evaluated on 5284 images. The final accuracy, precision, recall, specificity and F1 score were | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Independent University, Bangladesh (IUB) | en_US |
| dc.subject | kidney tumor recognition | en_US |
| dc.subject | computed tomography | en_US |
| dc.subject | deep convolutional neural networks | en_US |
| dc.subject | transfer learning | en_US |
| dc.title | Kidney Tumor Recognition from Abdominal CT Images using Transfer Learning | en_US |
| dc.type | Article | en_US |
