A survey on text classification algorithms: From text to predictions
In recent years, the exponential growth of digital documents has been met by rapid progress
in text classification techniques. Newly proposed machine learning algorithms leverage the …
in text classification techniques. Newly proposed machine learning algorithms leverage the …
[HTML][HTML] Current trends in deep learning for Earth Observation: An open-source benchmark arena for image classification
Abstract We present AiTLAS: Benchmark Arena–an open-source benchmark suite for
evaluating state-of-the-art deep learning approaches for image classification in Earth …
evaluating state-of-the-art deep learning approaches for image classification in Earth …
A principal odor map unifies diverse tasks in olfactory perception
Mapping molecular structure to odor perception is a key challenge in olfaction. We used
graph neural networks to generate a principal odor map (POM) that preserves perceptual …
graph neural networks to generate a principal odor map (POM) that preserves perceptual …
Fsd50k: an open dataset of human-labeled sound events
Most existing datasets for sound event recognition (SER) are relatively small and/or domain-
specific, with the exception of AudioSet, based on over 2 M tracks from YouTube videos and …
specific, with the exception of AudioSet, based on over 2 M tracks from YouTube videos and …
[HTML][HTML] PTB-XL, a large publicly available electrocardiography dataset
P Wagner, N Strodthoff, RD Bousseljot, D Kreiseler… - Scientific data, 2020 - nature.com
Electrocardiography (ECG) is a key non-invasive diagnostic tool for cardiovascular diseases
which is increasingly supported by algorithms based on machine learning. Major obstacles …
which is increasingly supported by algorithms based on machine learning. Major obstacles …
An artificial intelligence-based stacked ensemble approach for prediction of protein subcellular localization in confocal microscopy images
Predicting subcellular protein localization has become a popular topic due to its utility in
understanding disease mechanisms and developing innovative drugs. With the rapid …
understanding disease mechanisms and developing innovative drugs. With the rapid …
A review on multi-label learning algorithms
Multi-label learning studies the problem where each example is represented by a single
instance while associated with a set of labels simultaneously. During the past decade …
instance while associated with a set of labels simultaneously. During the past decade …
A tutorial on multilabel learning
E Gibaja, S Ventura - ACM Computing Surveys (CSUR), 2015 - dl.acm.org
Multilabel learning has become a relevant learning paradigm in the past years due to the
increasing number of fields where it can be applied and also to the emerging number of …
increasing number of fields where it can be applied and also to the emerging number of …
Clotho: An audio captioning dataset
K Drossos, S Lipping, T Virtanen - ICASSP 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
Audio captioning is the novel task of general audio content description using free text. It is an
intermodal translation task (not speech-to-text), where a system accepts as an input an …
intermodal translation task (not speech-to-text), where a system accepts as an input an …
[HTML][HTML] Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing
Objective Social determinants of health (SDOH) are non-medical factors that can profoundly
impact patient health outcomes. However, SDOH are rarely available in structured electronic …
impact patient health outcomes. However, SDOH are rarely available in structured electronic …