Also called Sigmoid Cross-Entropy loss. It is a Sigmoid activation plus a Cross-Entropy loss. Unlike Softmax loss it is independent for each ... ... <看更多>

In the constructor of tf.keras.losses.BinaryCrossentropy() , you'll notice, tf.keras.losses.BinaryCrossentropy( from_logits=False ... ... <看更多>

Binary cross-entropy is for multi-label classifications, whereas categorical cross entropy is for multi-class classification where each example belongs to a ... ... <看更多>

There is used Binary cross-entropy with Logistic activation (sigmoid) for multi-label classification in the Yolo v3, so each bonded box (each ... ... <看更多>

Computes the binary cross-entropy loss (log-loss) of two vectors. ... <看更多>