Transformer-based end-to-end classification of variable-length volumetric data.
Marzieh OghbaieTeresa AraujoTaha EmreUrsula Schmidt-ErfurthHrvoje BogunovicPublished in: CoRR (2023)
Keyphrases
- end to end
- variable length
- volumetric data
- fixed length
- pattern recognition
- congestion control
- text localization and recognition
- feature extraction
- machine learning
- feature vectors
- n gram
- feature selection
- medical imaging
- text classification
- multipath
- feature space
- computer vision
- bitstream
- image analysis
- high quality
- scalable video
- image sequences
- three dimensional