In this study, we present EBANO (Ensemble BAsed on uNimodal Ordinal classifiers), which
is a novel ensemble approach of ordinal classifiers that includes four soft labelling …

Deep learning techniques for ordinal classification have recently gained significant attention.
Predicting an ordinal variable, that is, a variable that demonstrates a natural relationship …

Dropout is a popular regularisation tool for deep neural classifiers, but it is applied
regardless of the nature of the classification task: nominal or ordinal. Consequently, the …

Abstract Decentralized Federated Learning improves data privacy and eliminates single
points of failure by removing reliance on centralized storage and model aggregation in …

Abstract dlordinal is a new Python library that unifies many recent deep ordinal classification
methodologies available in the literature. Developed using PyTorch as underlying …

This paper presents, for the first time, a distance metric learning algorithm for monotonic
classification. Monotonic datasets arise in many real-world applications, where there exist …

Distributed acoustic sensor network (DASN) refers to a sound acquisition system that
consists of a collection of microphones randomly distributed across a wide acoustic area …

This paper proposes a novel approach for modeling observational data in the form of expert
ratings, which are commonly given on an ordered (numerical or ordinal) scale. In practice …

Pose estimation is crucial to guide a visual harvesting robot to detach crops. In this article,
pose estimation for Sichuan peppers is formulated as an ordinal classification problem by …

Aesthetic quality control (AQC) is an essential step in smart factories to ensure that product
quality meets the desired standards. This operation includes assessing factors such as …