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MIT researchers develop an AI model that can detect future lung cancer risk（图）
人工智能模型 检测肺癌风险 深度学习
2023/6/20
The name Sybil has its origins in the oracles of Ancient Greece, also known as sibyls: feminine figures who were relied upon to relay divine knowledge of the unseen and the omnipotent past, present, a...
Artificial intelligence model can detect Parkinson’s from breathing patterns（图）
人工智能模型 呼吸模式 帕金森氏症
2023/6/20
Parkinson’s disease is notoriously difficult to diagnose as it relies primarily on the appearance of motor symptoms such as tremors, stiffness, and slowness, but these symptoms often appear several ye...
Cancer cells can have thousands of mutations in their DNA. However, only a handful of those actually drive the progression of cancer; the rest are just along for the ride.
Many of us easily recognize emotions expressed in others’ faces. A smile may mean happiness, while a frown may indicate anger. Autistic people often have a more difficult time with this task. It’s unc...
Sense, Model and Identify the Load Signatures of HVAC Systems in Metro Stations
Sense Model Identify Load Signatures HVAC Systems Metro Stations
2016/1/22
The Heating Ventilation and Air Conditioning(HVAC) systems in subway stations are energy consuming giants,each of which may consume over 10, 000 Kilowatts per day for cooling and ventilation. To save ...
Fast model predictive control using online optimization
Model predictive control application offline calculation network controller
2015/8/7
A widely recognized shortcoming of model predictive control (MPC) is that it can usually only be used in applications with slow dynamics, where the sample time is measured in seconds or minutes. A wel...
A modular network treatment of Baars' Global Workspace consciousness model
consciousness general cognitive model global workspace information theory phase transition random network
2015/7/31
Adapting techniques from random and semirandom network theory, this work provides an alternative to the renormalization and phase transition methods used in Wallace's (2005a) treatment of Baars' Globa...
A Quantitative Neural Coding Model of Sensory Memory
neural coding sensory memory synaptic plasticity lateral competition
2015/6/10
The coding mechanism of sensory memory on the neuron scale is one of the most important questions in neuroscience. We have put forward a quantitative neural network model, which is self-organized, sel...
Non-Negative Factor Analysis for Gaussian Mixture Model Weight Adaptation for Language and Dialect Recognition
Non-negative factor analysis model adaptation Gaussian mixture model weight dialect recognition language recognition
2014/11/27
Non-Negative Factor Analysis for Gaussian Mixture Model Weight Adaptation for Language and Dialect Recognition.
A Nonparametric Bayesian Approach to Acoustic Model Discovery
A Nonparametric Bayesian Approach Acoustic Model Discovery
2014/11/27
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneously segments the speec...
An Efferent-Inspired Auditory Model Front-End for Speech Recognition
efferent auditory model feature extraction
2014/11/27
In this paper, we investigate a closed-loop auditory model and explore its potential as a feature representation for speech recognition. The closed-loop representation consists of an auditory-based, e...
A Back-off Discriminative Acoustic Model for Automatic Speech Recognition
context-dependent acoustic modeling back-off acoustic models discriminative training
2014/11/27
In this paper we propose a back-off discriminative acoustic model for Automatic Speech Recognition (ASR). We use a set of broad phonetic classes to divide the classification problem originating from c...
LANGUAGE MODEL PARAMETER ESTIMATION USING USER TRANSCRIPTIONS
speech recognition, language modeling, adaptation
2014/11/27
In limited data domains, many effective language modeling techniques construct models with parameters to be estimated on an in-domain development set. However, in some domains, no such data exist beyo...
A Markov Model of Machine Translation using Non-parametric Bayesian Inference
Markov Model Machine Translation Non-parametric Bayesian Inference
2014/3/20
Most modern machine translation systems use phrase pairs as translation units, allowing for accurate modelling of phraseinternal translation and reordering. However phrase-based approaches are much le...
An Infinite Hierarchical Bayesian Model of Phrasal Translation
An Infinite Hierarchical Bayesian Model Phrasal Translation
2014/3/20
Modern phrase-based machine translation systems make extensive use of wordbased translation models for inducing alignments from parallel corpora. This is problematic, as the systems are incapable of a...