59 research outputs found
Heartbeat Anomaly Detection using Adversarial Oversampling
Cardiovascular diseases are one of the most common causes of death in the
world. Prevention, knowledge of previous cases in the family, and early
detection is the best strategy to reduce this fact. Different machine learning
approaches to automatic diagnostic are being proposed to this task. As in most
health problems, the imbalance between examples and classes is predominant in
this problem and affects the performance of the automated solution. In this
paper, we address the classification of heartbeats images in different
cardiovascular diseases. We propose a two-dimensional Convolutional Neural
Network for classification after using a InfoGAN architecture for generating
synthetic images to unbalanced classes. We call this proposal Adversarial
Oversampling and compare it with the classical oversampling methods as SMOTE,
ADASYN, and RandomOversampling. The results show that the proposed approach
improves the classifier performance for the minority classes without harming
the performance in the balanced classes
Additive Margin SincNet for Speaker Recognition
Speaker Recognition is a challenging task with essential applications such as
authentication, automation, and security. The SincNet is a new deep learning
based model which has produced promising results to tackle the mentioned task.
To train deep learning systems, the loss function is essential to the network
performance. The Softmax loss function is a widely used function in deep
learning methods, but it is not the best choice for all kind of problems. For
distance-based problems, one new Softmax based loss function called Additive
Margin Softmax (AM-Softmax) is proving to be a better choice than the
traditional Softmax. The AM-Softmax introduces a margin of separation between
the classes that forces the samples from the same class to be closer to each
other and also maximizes the distance between classes. In this paper, we
propose a new approach for speaker recognition systems called AM-SincNet, which
is based on the SincNet but uses an improved AM-Softmax layer. The proposed
method is evaluated in the TIMIT dataset and obtained an improvement of
approximately 40% in the Frame Error Rate compared to SincNet
Análise de atos de currículo na educação física em escolas da rede municipal de Simão Dias - SE e Paripiranga - BA
Atos de Currículo se constituem como toda e qualquer ação curricular planejada e desenvolvida pelos atores educacionais. Na Educação Física, estes vem sendo motivados e influenciados pelas teorias curriculares tradicionais, crítica e pós-critica. Este trabalho surge a partir das inquietações pautadas em quais teorias curriculares estão vinculados os Atos de Currículo na Educação Física escolar no ensino fundamental II em escolas da Bahia e Sergipe. Objetivamos analisar os planos de ensino da disciplina Educação Física, buscando vestígios das correntes teóricas. A metodologia caracterizada como pesquisa de abordagem qualitativa do tipo documental. Analisamos o conteúdo por categoria. O objeto de estudo foram os planos de ensino de dois professores (P1 e P2), do 6º e 9º ano de duas escolas (E1 e E2). Os resultados apontam certa dificuldade na organização dos planos. Ambos apontam para a repetição dos esportes coletivos como temas dominantes, pautados principalmente em concepções tradicionais do currículo. Concernindo à Educação Física escolar um papel reducionista de fomentar corpos biologicamente harmoniosos para o lazer, o trabalho e a aprendizagem de outros conhecimentos. Outro traço é a falta de progressão dos conteúdos a serem ensinados.
- …