Results 11 to 20 of about 1,760,183 (325)

Multimodal Grounding for Sequence-to-sequence Speech Recognition [PDF]

open access: yesICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
Humans are capable of processing speech by making use of multiple sensory modalities. For example, the environment where a conversation takes place generally provides semantic and/or acoustic context that helps us to resolve ambiguities or to recall named entities.
Caglayan, O   +4 more
openaire   +3 more sources

Recognition of Specific DNA Sequences [PDF]

open access: yesMolecular Cell, 2001
Proteins that recognize specific DNA sequences play a central role in the regulation of transcription. The tremendous increase in structural information on protein-DNA complexes has uncovered a remarkable structural diversity in DNA binding folds, while at the same time revealing common themes in binding to target sites in the genome.
Garvie, Colin W., Wolberger, Cynthia
openaire   +2 more sources

High-throughput profiling of sequence recognition by tyrosine kinases and SH2 domains using bacterial peptide display

open access: yeseLife, 2023
Tyrosine kinases and SH2 (phosphotyrosine recognition) domains have binding specificities that depend on the amino acid sequence surrounding the target (phospho)tyrosine residue.
Allyson Li   +4 more
doaj   +1 more source

Computational recognition of potassium channel sequences [PDF]

open access: yesBioinformatics, 2006
Abstract Motivation: Potassium channels are mainly known for their role in regulating and maintaining the membrane potential. Since this is one of the key mechanisms of signal transduction, malfunction of these potassium channels leads to a wide variety of severe diseases.
Heil, B.   +3 more
openaire   +3 more sources

End-to-End Sequence Labeling via Convolutional Recurrent Neural Network with a Connectionist Temporal Classification Layer

open access: yesInternational Journal of Computational Intelligence Systems, 2020
Sequence labeling is a common machine-learning task which not only needs the most likely prediction of label for a local input but also seeks the most suitable annotation for the whole input sequence.
Xiaohui Huang   +4 more
doaj   +1 more source

Recognition of signal sequences

open access: yesFEBS Letters, 1983
The hypothesis assumes that every continuous, entirely hydrophobic sequence of sufficient length, which is not involved in strong intramolecular contacts with other parts of the nascent protein chain, will function as a signal for translocation across the endoplasmic reticulum membrane or across the inner bacterial membrane.
Finkelstein, Alexei V.   +2 more
openaire   +2 more sources

Underwater Communication Signal Recognition Using Sequence Convolutional Network

open access: yesIEEE Access, 2021
Automatic modulation recognition (AMR) is one of the essential parts in the intelligent communication system. In the underwater acoustic communication, it is a challenging work that promptly and easily recognizes the signal modulation schemes by ...
Yan Wang   +6 more
doaj   +1 more source

Joining of Immunoglobulin Heavy Chain Gene Segments: Implications from a Chromosome with Evidence of Three D-JH Fusions [PDF]

open access: yes, 1982
A chromosomal segment with a unique structure around the immunoglobulin heavy chain joining region (JH) has been molecularly cloned from an Abelson murine leukemia virus-transformed cell line.
Alt, Frederick W., Baltimore, David
core   +1 more source

Sequence-to-Sequence Contrastive Learning for Text Recognition [PDF]

open access: yes2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
We propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual representations, which we apply to text recognition. To account for the sequence-to-sequence structure, each feature map is divided into different instances over which the contrastive loss is computed. This operation enables us to contrast in a sub-word level, where
Aberdam, Aviad   +7 more
openaire   +3 more sources

Research Status and Prospect of Transformer in Speech Recognition

open access: yesJisuanji kexue yu tansuo, 2021
As a new deep learning algorithm framework, Transformer has attracted more and more researchers?? attention and has become a current research hotspot. Inspired by humans focusing on important things only, the self-attention mechanism in the Transformer ...
ZHANG Xiaoxu, MA Zhiqiang, LIU Zhiqiang, ZHU Fangyuan, WANG Chunyu
doaj   +1 more source

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