Colorectal-cancer-detection-using-ColoPola-dataset
Methods
We trained and tested three models from scratch (CNN, CNN_2 and EfficientFormerV2) and two pretrained models (DenseNet121 and EfficientNetV2-m) to classify the colorectal cancer using the ColoPola dataset.
ColoPola dataset
The dataset consists of 572 slices (specimens) with 20,592 images. There are 284 cancer samples and 288 normal samples. This dataset can download from Zenodo repository. ...
Type: Python
Creators: Thi-Thu-Hien Pham, Thao-Vi Nguyen, The-Hiep Nguyen, Quoc-Hung Phan, Thanh-Hai Le
Submitter: Thanh-Hai Le
Name: Dislib Distributed Training - Cache OFF Contact Person: cristian.tatu@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: Minotauro-MN4
PyTorch distributed training of CNN on GPU. Launched using 32 GPUs (16 nodes). Dataset: Imagenet Version dislib-0.9 Version PyTorch 1.7.1+cu101
Average task execution time: 84 seconds
Type: COMPSs
Creators: Cristian Tatu, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)
Submitter: Cristian Tatu
Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data
In recent years, convolutional neural network (CNN)-based methods have shown remarkable performance in the denoising and reconstruction of super-resolved structured illumination microscopy (SR-SIM) data. Therefore, CNN-based architectures have been the main focus of existing studies. Recently, however, an alternative and highly competitive deep learning architecture, ...
