Papers Multi-class Classification
“Multi-class Classification” 태그가 달린 논문 1,009편 · 필터 해제
Geometric Calibration and Neutral Zones for Uncertainty-Aware Multi-Class Classification
Modern artificial intelligence systems make critical decisions yet often fail silently when uncertain -- even well-calibrated models provide no mechanism to identify \textit{which specific predictions} are unreliable. We…
Multi-class ClassificationData-Driven Assessment of Concrete Slab Integrity via Impact-Echo Signals and Neural Networks
Subsurface defects such as delamination, voids, and honeycombing critically affect the durability of concrete bridge decks but are difficult to detect reliably using visual inspection or manual sounding. This paper prese…
Multi-class ClassificationFairness Meets Privacy: Integrating Differential Privacy and Demographic Parity in Multi-class Classification
The increasing use of machine learning in sensitive applications demands algorithms that simultaneously preserve data privacy and ensure fairness across potentially sensitive sub-populations. While privacy and fairness h…
Multi-class ClassificationWaveFuse-AL: Cyclical and Performance-Adaptive Multi-Strategy Active Learning for Medical Images
Active learning reduces annotation costs in medical imaging by strategically selecting the most informative samples for labeling. However, individual acquisition strategies often exhibit inconsistent behavior across diff…
Multi-class ClassificationSkin Lesion SegmentationBinary ClassificationPneumonia DetectionBeyond Tsybakov: Model Margin Noise and $\mathcal{H}$-Consistency Bounds
We introduce a new low-noise condition for classification, the Model Margin Noise (MM noise) assumption, and derive enhanced $\mathcal{H}$-consistency bounds under this condition. MM noise is weaker than Tsybakov noise c…
Multi-class ClassificationTowards Reinforcement Learning from Neural Feedback: Mapping fNIRS Signals to Agent Performance
Reinforcement Learning from Human Feedback (RLHF) is a methodology that aligns agent behavior with human preferences by integrating user feedback into the agent's training process. This paper introduces a framework that …
Multi-class ClassificationReinforcement LearningA Brain Wave Encodes a Thousand Tokens: Modeling Inter-Cortical Neural Interactions for Effective EEG-based Emotion Recognition
Human emotions are difficult to convey through words and are often abstracted in the process; however, electroencephalogram (EEG) signals can offer a more direct lens into emotional brain activity. Recent studies show th…
Multi-class ClassificationEmotion RecognitionMMDCP: A Distribution-free Approach to Outlier Detection and Classification with Coverage Guarantees and SCW-FDR Control
We propose the Modified Mahalanobis Distance Conformal Prediction (MMDCP), a unified framework for multi-class classification and outlier detection under label shift, where the training and test distributions may differ.…
Multi-class ClassificationOutlier DetectionTowards classification-based representation learning for place recognition on LiDAR scans
Place recognition is a crucial task in autonomous driving, allowing vehicles to determine their position using sensor data. While most existing methods rely on contrastive learning, we explore an alternative approach by …
Multi-class ClassificationRepresentation LearningContrastive LearningAutonomous DrivingMSRANetV2: An Explainable Deep Learning Architecture for Multi-class Classification of Colorectal Histopathological Images
Colorectal cancer (CRC) is a leading worldwide cause of cancer-related mortality, and the role of prompt precise detection is of paramount interest in improving patient outcomes. Conventional diagnostic methods such as c…
Multi-class ClassificationAdaptive Forests For Classification
Random Forests (RF) and Extreme Gradient Boosting (XGBoost) are two of the most widely used and highly performing classification and regression models. They aggregate equally weighted CART trees, generated randomly in RF…
Multi-class ClassificationA supervised discriminant data representation: application to pattern classification
The performance of machine learning and pattern recognition algorithms generally depends on data representation. That is why, much of the current effort in performing machine learning algorithms goes into the design of p…
Multi-class ClassificationFrom Prototypes to Sparse ECG Explanations: SHAP-Driven Counterfactuals for Multivariate Time-Series Multi-class Classification
In eXplainable Artificial Intelligence (XAI), instance-based explanations for time series have gained increasing attention due to their potential for actionable and interpretable insights in domains such as healthcare. A…
Multi-class ClassificationECG ClassificationLung Cancer Classification from CT Images Using ResNet
Lung cancer, a malignancy originating in lung tissues, is commonly diagnosed and classified using medical imaging techniques, particularly computed tomography (CT). Despite the integration of machine learning and deep le…
Multi-class ClassificationCancer ClassificationBinary ClassificationFeature Selection and Regularization in Multi-Class Classification: An Empirical Study of One-vs-Rest Logistic Regression with Gradient Descent Optimization and L1 Sparsity Constraints
Multi-class wine classification presents fundamental trade-offs between model accuracy, feature dimensionality, and interpretability - critical factors for production deployment in analytical chemistry. This paper presen…
Multi-class ClassificationGTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection
The escalating complexity of network threats and the inherent class imbalance in traffic data present formidable challenges for modern Intrusion Detection Systems (IDS). While Graph Neural Networks (GNNs) excel in modeli…
Multi-class ClassificationIntrusion DetectionError correction in multiclass image classification of facial emotion on unbalanced samples
This paper considers the problem of error correction in multi-class classification of face images on unbalanced samples. The study is based on the analysis of a data frame containing images labeled by seven different emo…
Multi-class ClassificationImage ClassificationEmotion RecognitionObject-Centric Case-Based Reasoning via Argumentation
We introduce Slot Attention Argumentation for Case-Based Reasoning (SAA-CBR), a novel neuro-symbolic pipeline for image classification that integrates object-centric learning via a neural Slot Attention (SA) component wi…
Multi-class ClassificationImage ClassificationA Comparative Analysis of Ensemble-Based Machine Learning Approaches with Explainable AI for Multi-Class Intrusion Detection in Drone Networks
The growing integration of drones into civilian, commercial, and defense sectors introduces significant cybersecurity concerns, particularly with the increased risk of network-based intrusions targeting drone communicati…
Multi-class ClassificationIntrusion DetectionFeature ImportanceEfficient Breast and Ovarian Cancer Classification via ViT-Based Preprocessing and Transfer Learning
Cancer is one of the leading health challenges for women, specifically breast and ovarian cancer. Early detection can help improve the survival rate through timely intervention and treatment. Traditional methods of detec…
Multi-class ClassificationCancer ClassificationBinary ClassificationTransfer Learning