Papers Ordinal Classification
“Ordinal Classification” 태그가 달린 논문 92편 · 필터 해제
a theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes
This paper addresses the general problem of designing ordinal classification methods based on comparing actions with limiting boundaries of ordered classes (categories). The fundamental requirement of the method consists…
Ordinal ClassificationAffect-driven Ordinal Engagement Measurement from Video
In education and intervention programs, user engagement has been identified as a major factor in successful program completion. Automatic measurement of user engagement provides helpful information for instructors to mee…
Federated LearningOrdinal ClassificationProstate Tissue Grading with Deep Quantum Measurement Ordinal Regression
Prostate cancer (PCa) is one of the most common and aggressive cancers worldwide. The Gleason score (GS) system is the standard way of classifying prostate cancer and the most reliable method to determine the severity an…
Binary ClassificationClassificationGeneral ClassificationOrdinal Classification+3Stay on Topic, Please: Aligning User Comments to the Content of a News Article
Social scientists have shown that up to 50% if the content posted to a news article have no relation to its journalistic content. In this study we propose a classification algorithm to categorize user comments posted to …
ArticlesClassificationGeneral ClassificationOrdinal ClassificationRegression or Classification? New Methods to Evaluate No-Reference Picture and Video Quality Models
Video and image quality assessment has long been projected as a regression problem, which requires predicting a continuous quality score given an input stimulus. However, recent efforts have shown that accurate quality s…
General ClassificationImage Quality AssessmentOrdinal ClassificationregressionWER-BERT: Automatic WER Estimation with BERT in a Balanced Ordinal Classification Paradigm
Automatic Speech Recognition (ASR) systems are evaluated using Word Error Rate (WER), which is calculated by comparing the number of errors between the ground truth and the transcription of the ASR system. This calculati…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)ClassificationGeneral Classification+4YNU-HPCC at SemEval-2020 Task 10: Using a Multi-granularity Ordinal Classification of the BiLSTM Model for Emphasis Selection
In this study, we propose a multi-granularity ordinal classification method to address the problem of emphasis selection. In detail, the word embedding is learned from Embeddings from Language Model (ELMO) to extract fea…
Language ModelingLanguage ModellingOrdinal ClassificationAn Effectiveness Metric for Ordinal Classification: Formal Properties and Experimental Results
In Ordinal Classification tasks, items have to be assigned to classes that have a relative ordering, such as positive, neutral, negative in sentiment analysis. Remarkably, the most popular evaluation metrics for ordinal …
ClassificationGeneral ClassificationOrdinal ClassificationSentiment AnalysisA Supervised Machine Learning Model For Imputing Missing Boarding Stops In Smart Card Data
Public transport has become an essential part of urban existence with increased population densities and environmental awareness. Large quantities of data are currently generated, allowing for more robust methods to unde…
BIG-bench Machine LearningImputationOrdinal ClassificationTransfer LearningDetecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data
Massive amounts of satellite data have been gathered over time, holding the potential to unveil a spatiotemporal chronicle of the surface of Earth. These data allow scientists to investigate various important issues, suc…
Ordinal ClassificationTime SeriesTime Series AnalysisNon-parametric Uni-modality Constraints for Deep Ordinal Classification
We propose a new constrained-optimization formulation for deep ordinal classification, in which uni-modality of the label distribution is enforced implicitly via a set of inequality constraints over all the pairs of adja…
ClassificationGeneral ClassificationHistorical Color Image DatingOrdinal ClassificationDeep Sensor Fusion for Real-Time Odometry Estimation
Cameras and 2D laser scanners, in combination, are able to provide low-cost, light-weight and accurate solutions, which make their fusion well-suited for many robot navigation tasks. However, correct data fusion depends …
Ordinal ClassificationRobot NavigationSensor FusionTranslationSDNet: Semantically Guided Depth Estimation Network
Autonomous vehicles and robots require a full scene understanding of the environment to interact with it. Such a perception typically incorporates pixel-wise knowledge of the depths and semantic labels for each image fro…
Autonomous VehiclesDepth EstimationOrdinal ClassificationScene Understanding+1Cumulative link models for deep ordinal classification
This paper proposes a deep convolutional neural network model for ordinal regression by considering a family of probabilistic ordinal link functions in the output layer. The link functions are those used for cumulative l…
ClassificationGeneral ClassificationOrdinal ClassificationMental Fatigue Monitoring using Brain Dynamics Preferences
Driver's cognitive state of mental fatigue significantly affects driving performance and more importantly public safety. Previous studies leverage the response time (RT) as the metric for mental fatigue and aim at estima…
EEGElectroencephalogram (EEG)Ordinal ClassificationregressionA Novel Variational Autoencoder with Applications to Generative Modelling, Classification, and Ordinal Regression
We develop a novel probabilistic generative model based on the variational autoencoder approach. Notable aspects of our architecture are: a novel way of specifying the latent variables prior, and the introduction of an o…
ClassificationGeneral ClassificationOrdinal ClassificationregressionOCAPIS: R package for Ordinal Classification And Preprocessing In Scala
Ordinal Data are those where a natural order exist between the labels. The classification and pre-processing of this type of data is attracting more and more interest in the area of machine learning, due to its presence …
ClassificationGeneral ClassificationOrdinal ClassificationLabel Noise Filtering Techniques to Improve Monotonic Classification
The monotonic ordinal classification has increased the interest of researchers and practitioners within machine learning community in the last years. In real applications, the problems with monotonicity constraints are v…
ClassificationGeneral ClassificationOrdinal ClassificationSemEval-2018 Task 1: Affect in Tweets
We present the SemEval-2018 Task 1: Affect in Tweets, which includes an array of subtasks on inferring the affectual state of a person from their tweet. For each task, we created labeled data from English, Arabic, and Sp…
ClassificationEmotion ClassificationGeneral ClassificationOrdinal Classification+1UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets
This paper describes our system created for the SemEval-2018 Task 1: Affect in Tweets (AIT-2018). We participated in both the regression and the ordinal classification subtasks for emotion intensity detection in English,…
ClassificationGeneral ClassificationOrdinal ClassificationPOS+2