1 |
Regular languages extended with reduplication: Formal models, proofs and illustrations
|
|
Wang, Yang. - : eScholarship, University of California, 2021
|
|
BASE
|
|
Show details
|
|
2 |
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
3 |
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Referring Segmentation in Images and Videos with Cross-Modal Self-Attention Network ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
A Sequence-to-Sequence Approach to Dialogue State Tracking ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Assessment of Use and Fit of Face Masks Among Individuals in Public During the COVID-19 Pandemic in China
|
|
|
|
In: JAMA Netw Open (2021)
|
|
BASE
|
|
Show details
|
|
8 |
Dual Convolutional LSTM Network for Referring Image Segmentation ...
|
|
|
|
Abstract:
We consider referring image segmentation. It is a problem at the intersection of computer vision and natural language understanding. Given an input image and a referring expression in the form of a natural language sentence, the goal is to segment the object of interest in the image referred by the linguistic query. To this end, we propose a dual convolutional LSTM (ConvLSTM) network to tackle this problem. Our model consists of an encoder network and a decoder network, where ConvLSTM is used in both encoder and decoder networks to capture spatial and sequential information. The encoder network extracts visual and linguistic features for each word in the expression sentence, and adopts an attention mechanism to focus on words that are more informative in the multimodal interaction. The decoder network integrates the features generated by the encoder network at multiple levels as its input and produces the final precise segmentation mask. Experimental results on four challenging datasets demonstrate that the ... : 12 pages, accepted for publication in IEEE Transactions on Multimedia ...
|
|
Keyword:
Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences
|
|
URL: https://dx.doi.org/10.48550/arxiv.2001.11561 https://arxiv.org/abs/2001.11561
|
|
BASE
|
|
Hide details
|
|
10 |
Cross-Modal Self-Attention Network for Referring Image Segmentation ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
A critical review of 'English' in China's English education: How far can Chinese teachers embrace ELF?
|
|
|
|
BASE
|
|
Show details
|
|
12 |
DeepDDK: A Deep Learning based Oral-Diadochokinesis Analysis Software
|
|
|
|
In: IEEE EMBS Int Conf Biomed Health Inform (2019)
|
|
BASE
|
|
Show details
|
|
13 |
Translation Analysis of Metaphor Translation in the Black Slaves
|
|
|
|
In: Cross-Cultural Communication; Vol 15, No 4 (2019): Cross-Cultural Communication; 11-14 ; 1923-6700 ; 1712-8358 (2019)
|
|
BASE
|
|
Show details
|
|
14 |
Spelling Error Correction Using a Nested RNN Model and Pseudo Training Data ...
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Relations Between Self-Reported Daily-Life Fatigue, Hearing Status, and Pupil Dilation During a Speech Perception in Noise Task
|
|
|
|
In: Ear Hear (2018)
|
|
BASE
|
|
Show details
|
|
16 |
The Pupil Dilation Response During Speech Perception in Dark and Light: The Involvement of the Parasympathetic Nervous System in Listening Effort
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Immigrants’ Use of eHealth Services in the United States, National Health Interview Survey, 2011-2015
|
|
|
|
BASE
|
|
Show details
|
|
18 |
Relations between self-reported daily-life fatigue, hearing status and pupil dilation during a speech perception in noise task
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Relations between self-reported daily-life fatigue, hearing status, and pupil dilation during a speech perception in noise task
|
|
|
|
BASE
|
|
Show details
|
|
|
|