Partial multi-label learning (PML) is an emerging weakly supervised learning framework,
where each training example is associated with multiple candidate labels which are only …

Recommendation algorithms that incorporate techniques from deep learning are becoming
increasingly popular. Due to the structure of the data coming from recommendation domains …

Time-series classification (TSC) has attracted a lot of attention in pattern recognition,
because wide range of applications from different domains such as finance and health …

EEG-based human recognition is increasingly becoming a popular modality for biometric
authentication. Two important features of EEG signals are liveliness and the robustness …

Develo** multi-biometric systems using multi-modal signals is the recent trend in
biometric identification problem. Integrating heart and brain electrical signals (ECG and …

Heart abnormality or disease is one of the leading causes of mortality worldwide. Sound
signal produced by the mechanical activity of heart, known as phono-cardiogram (PCG) …

Hand vein biometric is an important modality for human authentication and liveness
detection in many applications. Reliable feature extraction is vital to any biometric system …

In the paper, Random Forest algorithm (RF), bagging and error-correction output code
model (ECOC) were employed to predict the clinic expenditure of infantile patients with data …

Construction methods for multi-valued classification (multi-class) systems using binary
classifiers are discussed and evaluated by a trade-off model for system evaluation based on …

Most real-world pattern recognition problems are too complex to be efficiently handled using
standard classification methods. Large number of classes or feature vectors, dataset …