You can ask for rationale or research questions specific to your dataset. If you want you can filter and process a specific cell type. (7) would return a python dictionary, type in that you want to label/annotate clusters for the processed cell type You can ask for reasoning, possible hyp...
Here, we propose a benchmark dataset that allows for quantifying explanation performance in a realistic magnetic resonance imaging (M RI) classification task. We employ this benchmark to understand the influence of transfer learning on the quality of explanations. Experimental results show tha t ...
python simple_extractor.py --dataset [DATASET] --model-restore [CHECKPOINT_PATH] --input-dir [INPUT_PATH] --output-dir [OUTPUT_PATH] TheDATASETcommand has three options, including 'lip', 'atr' and 'pascal'. Note each pixel in the output images denotes the predicted label number. The out...