We implemented Machine Learning (ML) techniques to advance the study of sperm whale (Physeter macrocephalus) bioacoustics. This entailed employing Convolutional Neural Networks (CNNs) to construct an echolocation click detector designed to classify spectrograms generated from sperm whale acoustic data accor...
from the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison. The funders had no role in study design, data collection and analysis, decision to publish or manuscript preparation. Author information Authors and Affiliations Department of Computer ...
This book has become an important reference for undergraduates, graduate students, and researchers. It presents the state of the field and the influence of... OB Yashchyk - Institute of Information Technologies and Learning Tools of NAES of Ukraine 被引量: 0发表: 2016年 Special Issue on Alan...
The remarkable flexibility and adaptability of ensemble methods and deep learning models have led to the proliferation of their application in bioinformatics research. Traditionally, these two machine learning techniques have largely been treated as independent methodologies in bioinformatics applications. Howeve...
(IGSP). In addition, a machine learning (ML) algorithm was introduced to help the IGSP detect and recognize the signals of breath samples to diagnose CHD. Due to the synergistic effect of BP and Ti3C2Txas well as photo excitation, the synthesized heterostructured complexes exhibited higher ...
We developed four machine learning-based CVD classifiers (i.e., multi-layer perceptron, support vector machine, random forest, and light gradient boosting) based on the Korea National Health and Nutrition Examination Survey. We resampled and rebalanced KNHANES data using complex sampling weights such...
In this study, four Artificial intelligence (AI) - based machine learning models were developed to estimate the Residual compressive strength (RCS) value of concrete supported with nano additives of Nanocarbon tubes (NCTs) and Nano alumina (NAl), after e
required of modern neuroscience methods. Objectives In this review, we discuss recent advances in the preclinical study of appetitive aggression in mice, paired with our perspective on the potential for machine learning techniques in producing automated, robust scoring of aggressive social behavior. We ...
In the recent 5 years (2014–2018), there has been growing interest in the use of machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic lesion changes within the area of neuroradiology. However, to date, the majority of research trend and current status have...
The model is trained for 5 × 105 epochs using the ADAM optimizer50 with a learning rate set to 5 × 10−4. The final residual of the fields predicted by the neural network are of the order of ~0.5, compared to the numerical residual produced by FDFD which is on the order...