Update README.md

README.md

@@ -279,23 +279,23 @@ configs:
   - split: test
     path: data/test-*
 ---
-# Dataset Card for QuickDraw Dataset
+# Dataset Card for TU Berline Dataset
 
-This dataset card aims to provide comprehensive information about the QuickDraw dataset, a collection of hand-drawn sketches used for training and evaluating sketch classification models.
+This dataset card aims to provide comprehensive information about the TU Berlin dataset, a collection of hand-drawn sketches used for training and evaluating sketch classification models.
 
 ## Dataset Details
 
 ### Dataset Description
 
-The QuickDraw dataset is a large-scale collection of hand-drawn sketches curated by the research team at TU Berlin. The dataset includes 20,000 unique sketches across 250 object categories, contributed by participants from around the world. The primary purpose of this dataset is to facilitate research in the field of computer vision, particularly for tasks related to sketch recognition and classification.
+The TU Berlin dataset is a large-scale collection of hand-drawn sketches curated by the research team at TU Berlin. The dataset includes 20,000 unique sketches across 250 object categories, contributed by participants from around the world. The primary purpose of this dataset is to facilitate research in the field of computer vision, particularly for tasks related to sketch recognition and classification.
 
 - **Curated by:** TU Berlin research team
 - **Shared by [optional]:** TU Berlin
 
 ### Dataset Sources
 
-- **Source:** [QuickDraw Dataset Source](https://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/)
-- **Paper:** [QuickDraw Dataset Paper](https://cybertron.cg.tu-berlin.de/eitz/pdf/2012_siggraph_classifysketch.pdf)
+- **Source:** [TU Berlin Dataset Source](https://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/)
+- **Paper:** [TU Berlin Dataset Paper](https://cybertron.cg.tu-berlin.de/eitz/pdf/2012_siggraph_classifysketch.pdf)
 
 ## Uses
 
@@ -320,7 +320,7 @@ The dataset is organized into categories, each containing a collection of hand-d
 
 ### Dataset Splits
 
-I downloaded the QuickDraw dataset and split it into train set, validation set, and test set.
+I downloaded the TU Berlin dataset and split it into train set, validation set, and test set.
 
 - **Train Set:**
   - **Number of Examples:** 16,000
@@ -349,7 +349,7 @@ val_data, test_data = train_test_split(temp_data, test_size=0.5, random_state=42
 
 ```bibtex
 @article{eitz2012hdhso,
-  title={QuickDraw: A large-scale sketch dataset for computer vision},
+  title={TU Berlin: A large-scale sketch dataset for computer vision},
   author={Eitz, Mathias and Hays, James and Alexa, Marc},
   journal={TU Berlin},
   year={2012}