Papers General Classification
“General Classification” 태그가 달린 논문 14,585편 · 필터 해제
AFINet: Attentive Feature Integration Networks for Image Classification
Convolutional Neural Networks (CNNs) have achieved tremendous success in a number of learning tasks including image classification. Recent advanced models in CNNs, such as ResNets, mainly focus on the skip connection to …
ClassificationGeneral Classificationimage-classificationImage ClassificationAn Autonomous Drone for Search and Rescue in Forests using Airborne Optical Sectioning
Drones will play an essential role in human-machine teaming in future search and rescue (SAR) missions. We present a first prototype that finds people fully autonomously in densely occluded forests. In the course of 17 f…
General ClassificationExamining and Mitigating Kernel Saturation in Convolutional Neural Networks using Negative Images
Neural saturation in Deep Neural Networks (DNNs) has been studied extensively, but remains relatively unexplored in Convolutional Neural Networks (CNNs). Understanding and alleviating the effects of convolutional kernel …
ClassificationData AugmentationGeneral ClassificationLoss-Aversively Fair Classification
The use of algorithmic (learning-based) decision making in scenarios that affect human lives has motivated a number of recent studies to investigate such decision making systems for potential unfairness, such as discrimi…
ClassificationDecision MakingFairnessGeneral ClassificationDiagSet: a dataset for prostate cancer histopathological image classification
Cancer diseases constitute one of the most significant societal challenges. In this paper, we introduce a novel histopathological dataset for prostate cancer detection. The proposed dataset, consisting of over 2.6 millio…
ClassificationGeneral ClassificationHistopathological Image Classificationimage-classification+1RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification
Real-world classification domains, such as medicine, health and safety, and finance, often exhibit imbalanced class priors and have asynchronous misclassification costs. In such cases, the classification model must achie…
General ClassificationGMOTE: Gaussian based minority oversampling technique for imbalanced classification adapting tail probability of outliers
Classification of imbalanced data is one of the common problems in the recent field of data mining. Imbalanced data substantially affects the performance of standard classification models. Data-level approaches mainly us…
ClusteringGeneral Classificationimbalanced classificationThe Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification
Using bag of words representations of time series is a popular approach to time series classification. These algorithms involve approximating and discretising windows over a series to form words, then forming a count of …
ClassificationGeneral ClassificationTime SeriesTime Series Analysis+1DocSCAN: Unsupervised Text Classification via Learning from Neighbors
We introduce DocSCAN, a completely unsupervised text classification approach using Semantic Clustering by Adopting Nearest-Neighbors (SCAN). For each document, we obtain semantically informative vectors from a large pre-…
ClassificationClusteringGeneral ClassificationLanguage Modeling+6Improving Patent Mining and Relevance Classification using Transformers
Patent analysis and mining are time-consuming and costly processes for companies, but nevertheless essential if they are willing to remain competitive. To face the overload induced by numerous patents, the idea is to aut…
ClassificationGeneral ClassificationPatent classificationChainNet: Neural Network-Based Successive Spectral Analysis
We discuss a new neural network-based direction of arrival estimation scheme that tackles the estimation task as a multidimensional classification problem. The proposed estimator uses a classification chain with as many …
ClassificationDirection of Arrival EstimationGeneral ClassificationPositionResMLP: Feedforward networks for image classification with data-efficient training
We present ResMLP, an architecture built entirely upon multi-layer perceptrons for image classification. It is a simple residual network that alternates (i) a linear layer in which image patches interact, independently a…
Data AugmentationFine-Grained Image ClassificationGeneral Classificationimage-classification+4Autoencoder Based Inter-Vehicle Generalization for In-Cabin Occupant Classification
Common domain shift problem formulations consider the integration of multiple source domains, or the target domain during training. Regarding the generalization of machine learning models between different car interiors,…
ClassificationGeneral ClassificationFew-Shot Learning for Image Classification of Common Flora
The use of meta-learning and transfer learning in the task of few-shot image classification is a well researched area with many papers showcasing the advantages of transfer learning over meta-learning in cases where data…
ClassificationFew-Shot Image ClassificationFew-Shot LearningGeneral Classification+5Diffusion Mechanism in Residual Neural Network: Theory and Applications
Diffusion, a fundamental internal mechanism emerging in many physical processes, describes the interaction among different objects. In many learning tasks with limited training samples, the diffusion connects the labeled…
Binary ClassificationClassificationFew-Shot Image ClassificationFew-Shot Learning+4The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification
It is evident that deep text classification models trained on human data could be biased. In particular, they produce biased outcomes for texts that explicitly include identity terms of certain demographic groups. We ref…
ClassificationFairnessGeneral Classificationtext-classification+1AdaBoost and robust one-bit compressed sensing
This paper studies binary classification in robust one-bit compressed sensing with adversarial errors. It is assumed that the model is overparameterized and that the parameter of interest is effectively sparse. AdaBoost …
Binary Classificationcompressed sensingGeneral ClassificationSoft-Attention Improves Skin Cancer Classification Performance
In clinical applications, neural networks must focus on and highlight the most important parts of an input image. Soft-Attention mechanism enables a neural network toachieve this goal. This paper investigates the effecti…
Cancer ClassificationClassificationGeneral ClassificationImage Classification+2Remote Pathological Gait Classification System
Several pathologies can alter the way people walk, i.e. their gait. Gait analysis can therefore be used to detect impairments and help diagnose illnesses and assess patient recovery. Using vision-based systems, diagnoses…
ClassificationGeneral ClassificationWalk in the Cloud: Learning Curves for Point Clouds Shape Analysis
Discrete point cloud objects lack sufficient shape descriptors of 3D geometries. In this paper, we present a novel method for aggregating hypothetical curves in point clouds. Sequences of connected points (curves) are in…
3D Part Segmentation3D Point Cloud ClassificationGeneral ClassificationPoint Cloud Classification