Vocal Bursts Type Prediction
155 papers with code • 1 benchmarks • 1 datasets
predict the type of given vocal bursts
Libraries
Use these libraries to find Vocal Bursts Type Prediction models and implementations
HUME-VB
Most implemented papers
Context-Dependent Fine-Grained Entity Type Tagging
We propose the task of context-dependent fine type tagging, where the set of acceptable labels for a mention is restricted to only those deducible from the local context (e. g. sentence or document).
Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding
Current systems of fine-grained entity typing use distant supervision in conjunction with existing knowledge bases to assign categories (type labels) to entity mentions.
Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss
billy-inn/NFETC
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NAACL 2018
The task of Fine-grained Entity Type Classification (FETC) consists of assigning types from a hierarchy to entity mentions in text.
SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification
Automatic classification of epileptic seizure types in electroencephalograms (EEGs) data can enable more precise diagnosis and efficient management of the disease.
Ludwig: a type-based declarative deep learning toolbox
uber/ludwig
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In this work we present Ludwig, a flexible, extensible and easy to use toolbox which allows users to train deep learning models and use them for obtaining predictions without writing code.
Typilus: Neural Type Hints
The network uses deep similarity learning to learn a TypeSpace -- a continuous relaxation of the discrete space of types -- and how to embed the type properties of a symbol (i. e. identifier) into it.
Vehicle and License Plate Recognition with Novel Dataset for Toll Collection
The best Mean Average Precision (mAP@0. 5) of 98. 8% for vehicle type recognition, 98. 5% for license plate detection, and 98. 3% for license plate reading is achieved by YOLOv4, while its lighter version, i. e., Tiny YOLOv4 obtained a mAP of 97. 1%, 97. 4%, and 93. 7% on vehicle type recognition, license plate detection, and license plate reading, respectively.
Car Type Recognition with Deep Neural Networks
In this paper we study automatic recognition of cars of four types: Bus, Truck, Van and Small car.
Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning
Motivation: State-of-the-art biomedical named entity recognition (BioNER) systems often require handcrafted features specific to each entity type, such as genes, chemicals and diseases.
Learning Type-Aware Embeddings for Fashion Compatibility
mvasil/fashion-compatibility
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ECCV 2018
Outfits in online fashion data are composed of items of many different types (e. g. top, bottom, shoes) that share some stylistic relationship with one another.
