Mindmap
Deep Learning Architectures
Inhalt der Mindmap
Deep Learning Architectures
Encoder / Decoder
- Encoder: Takes input and generates a high dimen. feature vector (feature representation)
- Decoder: Takes feature representation as input and generates output
- CNNs
- Example: Image Segmentation
- Example: Image Segmentation
- RNNs
- Mixed Style (CNN + RNN)
- CNNs
- Decoder: Takes feature representation as input and generates output
- Encoder: Takes input and generates a high dimen. feature vector (feature representation)
Transformer
- No Encoder/Decoder, just Attention Mechanism
- No Encoder/Decoder, just Attention Mechanism
RNN
- LSTM
- GRU
Informationen
- Beschreibung
- Mindmap am Deep Learning Architectures, erstellt von Sophokles Ktistakis am 26/11/2018.
- Erstellt von
- Sophokles Ktistakis
- Aufrufe
- 2
- Bewertung