fix minor typo on the image segmentation tutorial

Just found that tf.keras.losses.CategoricalCrossentropy should be changed to tf.keras.losses.SparseCategoricalCrossentropy since the pixel classes (labels) are integers, not one-hot encoded. Code is written correct, but the markdown should fix to prevent potential confusion to readers.

Author: Jihun Han

site/en/tutorials/images/segmentation.ipynb

@@ -452,7 +452,7 @@
         "\n",
         "Now, all that is left to do is to compile and train the model. \n",
         "\n",
-        "Since this is a multiclass classification problem, use the `tf.keras.losses.CategoricalCrossentropy` loss function with the `from_logits` argument set to `True`, since the labels are scalar integers instead of vectors of scores for each pixel of every class.\n",
+        "Since this is a multiclass classification problem, use the `tf.keras.losses.SparseCategoricalCrossentropy` loss function with the `from_logits` argument set to `True`, since the labels are scalar integers instead of vectors of scores for each pixel of every class.\n",
         "\n",
         "When running inference, the label assigned to the pixel is the channel with the highest value. This is what the `create_mask` function is doing."
       ]