Papers Hierarchical Multi-label Classification
“Hierarchical Multi-label Classification” 태그가 달린 논문 56편 · 필터 해제
Taxlifier: Leveraging Disease Taxonomy for Enhanced Multi-Label Classification in Chest Radiography
Accurate and efficient classification of thoracic diseases in chest X-ray (CXR) images is crucial for timely diagnosis and treatment. However, the presence of multiple pathologies with overlapping visual characteristics …
Hierarchical Multi-label ClassificationEvaluation Sovereignty in Metadata-Driven Classification: A Multi-Track Framework for Weakly Supervised Information Systems
Evaluation in machine learning is typically treated as a neutral measurement process. However, in operational information systems, evaluation outcomes are often conditioned by the processes used to generate labels. This …
Hierarchical Multi-label ClassificationMAPLE: Multi-Path Adaptive Propagation with Level-Aware Embeddings for Hierarchical Multi-Label Image Classification
Hierarchical multi-label classification (HMLC) is essential for modeling structured label dependencies in remote sensing. Yet existing approaches struggle in multi-path settings, where images may activate multiple taxono…
Hierarchical Multi-label ClassificationMulti-Label Image ClassificationHELM: Hierarchical and Explicit Label Modeling with Graph Learning for Multi-Label Image Classification
Hierarchical multi-label classification (HMLC) is essential for modeling complex label dependencies in remote sensing. Existing methods, however, struggle with multi-path hierarchies where instances belong to multiple br…
Hierarchical Multi-label ClassificationMulti-Label Image ClassificationGraph LearningAn Analysis of Multi-Task Architectures for the Hierarchic Multi-Label Problem of Vehicle Model and Make Classification
Most information in our world is organized hierarchically; however, many Deep Learning approaches do not leverage this semantically rich structure. Research suggests that human learning benefits from exploiting the hiera…
Hierarchical Multi-label ClassificationMulti-Task LearningImproving Detection of Rare Nodes in Hierarchical Multi-Label Learning
In hierarchical multi-label classification, a persistent challenge is enabling model predictions to reach deeper levels of the hierarchy for more detailed or fine-grained classifications. This difficulty partly arises fr…
Hierarchical Multi-label ClassificationMulti-Label LearningEnhancing Multimodal Protein Function Prediction Through Dual-Branch Dynamic Selection with Reconstructive Pre-Training
Multimodal protein features play a crucial role in protein function prediction. However, these features encompass a wide range of information, ranging from structural data and sequence features to protein attributes and …
Hierarchical Multi-label ClassificationProtein Function PredictionHierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-Label Classification
Hierarchical Multi-Label Classification (HMC) faces critical challenges in maintaining structural consistency and balancing loss weighting in Multi-Task Learning (MTL). In order to address these issues, we propose a clas…
Hierarchical Multi-label ClassificationContrastive LearningMulti-Task LearningClinically-Inspired Hierarchical Multi-Label Classification of Chest X-rays with a Penalty-Based Loss Function
In this work, we present a novel approach to multi-label chest X-ray (CXR) image classification that enhances clinical interpretability while maintaining a streamlined, single-model, single-run training pipeline. Leverag…
Hierarchical Multi-label Classificationimage-classificationImage ClassificationMulti-Label Classification+1Can Large Language Models Serve as Effective Classifiers for Hierarchical Multi-Label Classification of Scientific Documents at Industrial Scale?
We address the task of hierarchical multi-label classification (HMC) of scientific documents at an industrial scale, where hundreds of thousands of documents must be classified across thousands of dynamic labels. The rap…
ClassificationDocument ClassificationHierarchical Multi-label ClassificationMulti-Label Classification+1Acoustic identification of individual animals with hierarchical contrastive learning
Acoustic identification of individual animals (AIID) is closely related to audio-based species classification but requires a finer level of detail to distinguish between individual animals within the same species. In thi…
ClassificationContrastive LearningHierarchical Multi-label ClassificationMulti-Label Classification+2Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery
In this work, we apply state-of-the-art self-supervised learning techniques on a large dataset of seafloor imagery, \textit{BenthicNet}, and study their performance for a complex hierarchical multi-label (HML) classifica…
Hierarchical Multi-label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONSelf-Supervised LearningHierarchy-aware Biased Bound Margin Loss Function for Hierarchical Text Classification
Hierarchical text classification (HTC) is a challenging problem with two key issues: utilizing structural information and mitigating label imbalance. Recently, the unit-based approach generating unit-based feature repres…
Hierarchical Multi-label ClassificationMulti-Label Classificationtext-classificationText ClassificationError Detection and Constraint Recovery in Hierarchical Multi-Label Classification without Prior Knowledge
Recent advances in Hierarchical Multi-label Classification (HMC), particularly neurosymbolic-based approaches, have demonstrated improved consistency and accuracy by enforcing constraints on a neural model during trainin…
Hierarchical Multi-label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONHierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation
Safety-critical applications such as autonomous driving require robust 3D environment perception algorithms capable of handling diverse and ambiguous surroundings. The predictive performance of classification models is h…
3D Semantic SegmentationAutonomous DrivingHierarchical Multi-label ClassificationLIDAR Semantic Segmentation+3IITK at SemEval-2024 Task 4: Hierarchical Embeddings for Detection of Persuasion Techniques in Memes
Memes are one of the most popular types of content used in an online disinformation campaign. They are primarily effective on social media platforms since they can easily reach many users. Memes in a disinformation campa…
Binary ClassificationClassificationHierarchical Multi-label ClassificationMeme Classification+3BCAmirs at SemEval-2024 Task 4: Beyond Words: A Multimodal and Multilingual Exploration of Persuasion in Memes
Memes, combining text and images, frequently use metaphors to convey persuasive messages, shaping public opinion. Motivated by this, our team engaged in SemEval-2024 Task 4, a hierarchical multi-label classification task…
Caption GenerationHierarchical Multi-label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONHierarchical Multi-label Classification for Fine-level Event Extraction from Aviation Accident Reports
A large volume of accident reports is recorded in the aviation domain, which greatly values improving aviation safety. To better use those reports, we need to understand the most important events or impact factors accord…
Event ExtractionHierarchical Multi-label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONHILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text Classification
Existing self-supervised methods in natural language processing (NLP), especially hierarchical text classification (HTC), mainly focus on self-supervised contrastive learning, extremely relying on human-designed augmenta…
Contrastive LearningDocument EmbeddingHierarchical Multi-label ClassificationRepresentation Learning+2Hierarchical Multi-Label Classification of Online Vaccine Concerns
Vaccine concerns are an ever-evolving target, and can shift quickly as seen during the COVID-19 pandemic. Identifying longitudinal trends in vaccine concerns and misinformation might inform the healthcare space by helpin…
ClassificationHierarchical Multi-label ClassificationMisinformationMulti-Label Classification+1