Results 41 to 50 of about 1,760,183 (325)
Sequence Classification Using Statistical Pattern Recognition [PDF]
, 2007 Proceeding of: 7th International Symposium on Intelligent Data Analysis. IDA-2007. Ljubljana, Slovenia, September, 6th-8th, 2007. Sequence classification is a significant problem that arises in many different real-world applications. The purpose of a sequence classifier is to assign a class label to a given sequence.
Iglesias Martínez, José Antonio +2 more
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S_T_Mamba: A Novel Jinnan Calf Diarrhea Behavior Recognition Model Based on Sequence Tree Mamba
AnimalsThe efficient and precise recognition of diarrhea-related behaviors in Jinnan calves is crucial for ensuring their healthy development. Nevertheless, conventional behavior recognition techniques are often limited by a notable decline in performance when ...
Wangli Hao +7 more
doaj +1 more source
Analysis of Multilingual Sequence-to-Sequence Speech Recognition Systems [PDF]
Interspeech 2019, 2019 This paper investigates the applications of various multilingual approaches developed in conventional hidden Markov model (HMM) systems to sequence-to-sequence (seq2seq) automatic speech recognition (ASR). On a set composed of Babel data, we first show the effectiveness of multi-lingual training with stacked bottle-neck (SBN) features.
Karafiát, Martin +5 more
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Cognitively Economical Heuristic for Multiple Sequence Alignment under Uncertainties
Axioms, 2022 This paper introduces a heuristic for multiple sequence alignment aimed at improving real-time object recognition in short video streams with uncertainties.
Milan Gnjatović +5 more
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State-of-the-art Speech Recognition With Sequence-to-Sequence Models
, 2018 Attention-based encoder-decoder architectures such as Listen, Attend, and Spell (LAS), subsume the acoustic, pronunciation and language model components of a traditional automatic speech recognition (ASR) system into a single neural network.
Bacchiani, Michiel +13 more
core +1 more source
Action recognition using vague division DMMs
The Journal of Engineering, 2017 This study presents a novel human action recognition method based on the sequences of depth maps, which provide additional body shape and motion information for action recognition.
Ke Jin +4 more
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Follower: A Novel Self-Deployable Action Recognition Framework
Sensors, 2021 Deep learning technology has improved the performance of vision-based action recognition algorithms, but such methods require a large number of labeled training datasets, resulting in weak universality.
Xu Yang +5 more
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Sequence-to-Sequence Models Can Directly Translate Foreign Speech
, 2017 We present a recurrent encoder-decoder deep neural network architecture that directly translates speech in one language into text in another. The model does not explicitly transcribe the speech into text in the source language, nor does it require ...
Chen, Zhifeng +4 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga +56 more
wiley +1 more source
A Novel Face Segmentation Algorithm from a Video Sequence for Real-Time Face Recognition
EURASIP Journal on Advances in Signal Processing, 2007 The first step in an automatic face recognition system is to localize the face region in a cluttered background and carefully segment the face from each frame of a video sequence. In this paper, we propose a fast and efficient algorithm for segmenting a
Sudhaker Samuel RD, Srikantaswamy R
doaj +2 more sources