Exploring the Capabilities of Quantum Support Vector Machines for Image Classification on the MNIST Benchmark.
Mateusz SlyszKrzysztof KurowskiGrzegorz WaligóraJan WeglarzPublished in: ICCS (5) (2023)
Keyphrases
- image classification
- support vector
- large margin classifiers
- learning machines
- svm classifier
- svm classification
- bag of words
- handwritten digits
- image representation
- visual features
- visual words
- multi class
- image features
- binary classification
- quantum computation
- feature extraction
- handwritten digit recognition
- class specific
- support vector machine
- classification accuracy
- digit recognition
- support vectors
- benchmark suite
- bag of features
- kernel function
- training examples
- model selection
- object detection
- multi label
- kernel methods
- radial basis function
- generalization ability
- multi class classification
- quantum computing
- probability ranking principle
- quantum inspired
- machine learning
- processing capabilities
- maximum margin
- support vector regression
- cross validation
- loss function
- support vector machine svm
- feature vectors
- similarity measure
- feature selection