Papers Multi-class Classification
“Multi-class Classification” 태그가 달린 논문 1,008편 · 필터 해제
Multi-label versus multi-class classification of blood cells and their aggregates in microfluidic channels
Deformability cytometry (DC) is a type of imaging flow cytometry, which uses a camera-equipped device to measure cellular stiffness in addition to other cellular properties at high throughput. Cellular properties such as…
Multi-class ClassificationFairness in multi-class multi-group classification problems via contextial coherent risk measures
We propose a new design of fair classifiers for multi-class classification problems in the presence of vector-valued sensitive attributes. In that scenario each sensitive attribute has multiple values and forms several g…
Multi-class ClassificationOn the Structure of Address in Multi-Party Dialogue: From Discrete Labels to Continuous Levels
In multi-party dialogues between a dialogue system and multiple users, identifying to whom an utterance is addressed is a key challenge. Prior work has typically treated addressee detection as a multi-class classificatio…
Multi-class ClassificationWhen does distribution shift break graph neural networks calibration?
Graph neural networks (GNNs) are increasingly deployed in real-world applications where distribution shift is un-avoidable. However, how such shifts affect model calibration, defined as the agreement between predictive c…
Multi-class ClassificationA Multi-cluster Boundary Learning Method for Out-of-Scope Intent Detection via MiniLM Embedding
Intent detection is a critical task that bridges human intents and system actions in human-machine interaction systems. However, there still exist challenges for detecting out-of-scope (OOS) intents. (i) The traditional …
Multi-class ClassificationIntent DetectionBe Indiscrete: The Benefits of Learning Continuous Spine Degeneration Severity Scores
Lumbar spine degeneration is a major contributor to chronic low back pain and is routinely assessed on MRI using ordinal grading systems, e.g. normal, mild, moderate, severe. Consequently, most approaches to train models…
Multi-class ClassificationGradient boosting with vector-valued leafs
Gradient boosting in the form of decision tree ensembles has successfully been applied to a variety of problems using simple objective functions based on log-likelihoods of a single variable. The concept extends naturall…
Multi-class ClassificationPredicting Poets' Origins from Verse: A Computational Analysis of Regional Linguistic Fingerprints in the Complete Tang Poems
We ask whether the geographic origin of Tang-dynasty poets leaves a detectable linguistic trace in their work. Aggregating every poem attributed to each author in the Complete Tang Poems (Quan Tang Shi) and linking poets…
Interpretable Machine LearningMulti-class ClassificationMitigating Measurement-Induced Training Instability in Hybrid Quantum Neural Networks for Protein Classification
Hybrid Quantum Neural Network (QNN) classifiers produce logits as expectation values of quantum measurement operators. For standard Pauli measurements, these outputs are intrinsically bounded to the interval [-1,1]. When…
Multi-class ClassificationSAGE: An Expert-Annotated South Asian GI Endoscopy Dataset for Multimodal Learning and Hallucination Analysis
Gastrointestinal cancers represent a growing health burden in the South Asian region, driven largely by rapid changes in socio-economic conditions and lifestyle habits. However, early diagnosis remains limited by inadequ…
Multi-Label ClassificationMulti-class ClassificationVisual Question AnsweringImage CaptioningEnhancing Precision Agriculture with a Hybrid Deep Learning Framework for Multi-Class Plant Disease Classification and Interpretability
This study proposes an overall deep learning architecture for multi-class classification of plant diseases from high-resolution leaf imagery, with a particular interest in investigating the behavior of ResNet-50 and a hy…
Multi-class ClassificationData AugmentationREMEDI: A Benchmark for Retention and Unlearning Evaluation in Multi-label Clinical Disease Inference
Language models trained for clinical disease inference are trained on patient data, which may include sensitive and private information, and data owners may request the removal of their data from a trained model due to p…
Multi-Label ClassificationMulti-class ClassificationAn Improved CNN-LSTM Based Intrusion Detection System for IoT Networks
With the rapid proliferation of IoT devices, security concerns have dramatically escalated and intrusion detection systems have become critical for protecting networked environments. This paper presents an improved CNN-L…
Multi-class ClassificationIntrusion DetectionA Hybrid Approach For Malware Classification Using Secondary Features Fusion
The number of malware (either variant or novel) is rapidly increasing, making malware detection and mitigation a complex problem. One approach to improving malware mitigation is automatic detection and malware family cla…
Multi-class ClassificationMalware ClassificationMalware DetectionDemystifying the Optimal Fair Classifier in Multi-Class Classification
Ensuring fair and equitable treatment across diverse groups, particularly in multi-class classification tasks, poses a significant challenge due to the persistent biases inherent in machine learning models. Most existing…
Multi-class ClassificationFrom Detection to Mechanism: Cross-Attention Graph Neural Networks Enable Drug-Drug Interaction Type Prediction An Ablation Study with Acetylsalicylic Acid Validation
Predicting whether two drugs interact (binary detection) is a substantially dif- ferent task from predicting the mechanism type of that interaction (multi-class classification). This study presents a systematic ablation …
Multi-class ClassificationGraph Neural NetworkType predictionMultimodal Graph-based Classification of Esophageal Motility Disorders
Diagnosing esophageal motility disorders pose significant challenges due to the complexity of high-resolution impedance manometry (HRIM) data and variability in clinical interpretation. This work explores the feasibility…
Multi-class ClassificationGraph Neural NetworkHyperspherical Forward-Forward with Prototypical Representations
The Forward-Forward (FF) algorithm presents a compelling, bio-inspired alternative to backpropagation. However, while efficient in training, it has a computationally prohibitive inference process that requires a separate…
Multi-class ClassificationImage ClassificationTransfer LearningFruitProM-V2: Robust Probabilistic Maturity Estimation and Detection of Fruits and Vegetables
Accurate fruit maturity identification is essential for determining harvest timing, as incorrect assessment directly affects yield and post-harvest quality. Although ripening is a continuous biological process, vision-ba…
Multi-class ClassificationAuditing LLMs for Algorithmic Fairness in Casenote-Augmented Tabular Prediction
LLMs are increasingly being considered for prediction tasks in high-stakes social service settings, but their algorithmic fairness properties in this context are poorly understood. In this short technical report, we audi…
Multi-class Classification