Results 31 to 40 of about 2,954,755 (181)
Validating deep learning seabed classification via acoustic similarity [PDF]
JASA Express Letters, 2021 While seabed characterization methods have often focused on estimating individual sediment parameters, deep learning suggests a class-based approach focusing on the overall acoustic effect.
David J. Forman +3 more
doaj +1 more source
Anomalous pattern based clustering of mental tasks with subject independent learning – some preliminary results [PDF]
, 2012 In this paper we describe a new method for EEG signal classification in which the classification of one subject’s EEG signals is based on features learnt from another subject.
Amorim, Renato +2 more
core +1 more source
Metropolis-Hastings via Classification
, 2021 This paper develops a Bayesian computational platform at the interface between posterior sampling and optimization in models whose marginal likelihoods are difficult to evaluate. Inspired by adversarial optimization, namely Generative Adversarial Networks (GAN), we reframe the likelihood function estimation problem as a classification problem.
Kaji, Tetsuya, Rockova, Veronika
openaire +2 more sources
Multi-View Classification via Adaptive Discriminant Analysis
IEEE Access, 2019 In many real applications, an object is usually represented with multiple views, providing compatible and complementary information to each other. Therefore, it is highly desirable to recognize the object from distinct and even heterogeneous views.
Deyan Xie +5 more
doaj +1 more source
On Classification of QCD defects via holography
, 2009 We discuss classification of defects of various codimensions within a holographic model of pure Yang-Mills theories or gauge theories with fundamental matter.
Alexander S. Gorsky +7 more
core +1 more source
Automated imbalanced classification via layered learning
Machine Learning, 2022 In this paper we address imbalanced binary classification (IBC) tasks. Applying resampling strategies to balance the class distribution of training instances is a common approach to tackle these problems. Many state-of-the-art methods find instances of interest close to the decision boundary to drive the resampling process.
Cerqueira, Vitor +3 more
openaire +3 more sources
Robust Multiple Signal Classification via Probability Measure Transformation
, 2015 In this paper, we introduce a new framework for robust multiple signal classification (MUSIC). The proposed framework, called robust measure-transformed (MT) MUSIC, is based on applying a transform to the probability distribution of the received signals,
Hero, Alfred O., Todros, Koby
core +1 more source
Utilizing MFCCs and TEO-MFCCs to Classify Stress in Females Using SSNNA
International Islamic University Malaysia Engineering JournalAll individuals are susceptible to experiencing stress in their everyday lives. Nevertheless, stress has a greater influence on females due to both biological and environmental factors.
Nur Aishah Zainal +5 more
doaj +1 more source
Imbalanced Classification via Feature Dictionary-Based Minority Oversampling
IEEE Access, 2022 Image classification research is one of the fields continuously studied in the computer vision domain, and several related studies have been actively conducted until recently.
Minho Park, Hwa Jeon Song, Dong-Oh Kang
doaj +1 more source
, 2006 Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised manner, and to use this object distribution to perform scene classification.
Bosch, A, Zisserman, A, Muñoz, X
openaire +2 more sources