Papers General Classification
“General Classification” 태그가 달린 논문 14,585편 · 필터 해제
Sentiment and Emotion Classification of Epidemic Related Bilingual data from Social Media
In recent years, sentiment analysis and emotion classification are two of the most abundantly used techniques in the field of Natural Language Processing (NLP). Although sentiment analysis and emotion classification are …
Emotion ClassificationGeneral ClassificationSentiment AnalysisOvarian Cancer Detection based on Dimensionality Reduction Techniques and Genetic Algorithm
In this research, we have two serum SELDI (surface-enhanced laser desorption and ionization) mass spectra (MS) datasets to be used to select features amongst them to identify proteomic cancerous serums from normal serums…
ClassificationDimensionality ReductionGeneral ClassificationDeep Neural Network for Musical Instrument Recognition using MFCCs
The task of efficient automatic music classification is of vital importance and forms the basis for various advanced applications of AI in the musical domain. Musical instrument recognition is the task of instrument iden…
General ClassificationInstrument RecognitionMusic ClassificationCausality-based Counterfactual Explanation for Classification Models
Counterfactual explanation is one branch of interpretable machine learning that produces a perturbation sample to change the model's original decision. The generated samples can act as a recommendation for end-users to a…
ClassificationcounterfactualCounterfactual ExplanationGeneral Classification+1LFI-CAM: Learning Feature Importance for Better Visual Explanation
Class Activation Mapping (CAM) is a powerful technique used to understand the decision making of Convolutional Neural Network (CNN) in computer vision. Recently, there have been attempts not only to generate better visua…
ClassificationDecision MakingFeature ImportanceGeneral Classification+2Heart-Darts: Classification of Heartbeats Using Differentiable Architecture Search
Arrhythmia is a cardiovascular disease that manifests irregular heartbeats. In arrhythmia detection, the electrocardiogram (ECG) signal is an important diagnostic technique. However, manually evaluating ECG signals is a …
Arrhythmia DetectionClassificationDiagnosticECG Classification+2Spectral Machine Learning for Pancreatic Mass Imaging Classification
We present a novel spectral machine learning (SML) method in screening for pancreatic mass using CT imaging. Our algorithm is trained with approximately 30,000 images from 250 patients (50 patients with normal pancreas a…
BIG-bench Machine LearningClassificationComputational EfficiencyCPU+1Weighted Least Squares Twin Support Vector Machine with Fuzzy Rough Set Theory for Imbalanced Data Classification
Support vector machines (SVMs) are powerful supervised learning tools developed to solve classification problems. However, SVMs are likely to perform poorly in the classification of imbalanced data. The rough set theory …
ClassificationGeneral ClassificationAGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy
Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is cruc…
AnatomyGeneral ClassificationSubspace Representation Learning for Few-shot Image Classification
In this paper, we propose a subspace representation learning (SRL) framework to tackle few-shot image classification tasks. It exploits a subspace in local CNN feature space to represent an image, and measures the simila…
ClassificationDiversityFew-Shot Image ClassificationGeneral Classification+4Enhancing Fine-Grained Classification for Low Resolution Images
Low resolution fine-grained classification has widespread applicability for applications where data is captured at a distance such as surveillance and mobile photography. While fine-grained classification with high resol…
AttributeClassificationGeneral ClassificationGM-MLIC: Graph Matching based Multi-Label Image Classification
Multi-Label Image Classification (MLIC) aims to predict a set of labels that present in an image. The key to deal with such problem is to mine the associations between image contents and labels, and further obtain the co…
ClassificationGeneral ClassificationGraph Matchingimage-classification+2Deep Image Destruction: Vulnerability of Deep Image-to-Image Models against Adversarial Attacks
Recently, the vulnerability of deep image classification models to adversarial attacks has been investigated. However, such an issue has not been thoroughly studied for image-to-image tasks that take an input image and g…
ClassificationColorizationDeblurringDenoising+3Out-of-Scope Domain and Intent Classification through Hierarchical Joint Modeling
User queries for a real-world dialog system may sometimes fall outside the scope of the system's capabilities, but appropriate system responses will enable smooth processing throughout the human-computer interaction. Thi…
ClassificationGeneral Classificationintent-classificationIntent Classification+1Flow-Packet Hybrid Traffic Classification for Class-Aware Network Routing
Network traffic classification using machine learning techniques has been widely studied. Most existing schemes classify entire traffic flows, but there are major limitations to their practicality. At a network router, t…
BIG-bench Machine LearningClassificationGeneral ClassificationTraffic ClassificationLocality Constrained Analysis Dictionary Learning via K-SVD Algorithm
Recent years, analysis dictionary learning (ADL) and its applications for classification have been well developed, due to its flexible projective ability and low classification complexity. With the learned analysis dicti…
ClassificationDictionary LearningGeneral Classificationimage-classification+1GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection
In this paper, a multi-scale visual transformer model, referred as GasHis-Transformer, is proposed for Gastric Histopathological Image Detection (GHID), which enables the automatic global detection of gastric cancer imag…
Adversarial AttackGeneral ClassificationHistopathological Image ClassificationImage Classification+1Fine-grained Generalization Analysis of Vector-valued Learning
Many fundamental machine learning tasks can be formulated as a problem of learning with vector-valued functions, where we learn multiple scalar-valued functions together. Although there is some generalization analysis on…
Extreme Multi-Label ClassificationGeneral ClassificationGeneralization BoundsMulti-class Classification+2Cross-Domain Few-Shot Classification via Adversarial Task Augmentation
Few-shot classification aims to recognize unseen classes with few labeled samples from each class. Many meta-learning models for few-shot classification elaborately design various task-shared inductive bias (meta-knowled…
ClassificationCross-Domain Few-ShotDomain GeneralizationGeneral Classification+2Graph-Embedded Subspace Support Vector Data Description
In this paper, we propose a novel subspace learning framework for one-class classification. The proposed framework presents the problem in the form of graph embedding. It includes the previously proposed subspace one-cla…
General ClassificationGraph EmbeddingOne-Class Classification