Results 71 to 80 of about 511,753 (356)

AI Education Matters: Teaching Hidden Markov Models

, 2018
In this column, we share resources for learning about and teaching Hidden Markov Models (HMMs). HMMs find many important applications in temporal pattern recognition tasks such as speech/handwriting/gesture recognition and robot localization.
Neller, Todd W.
core   +1 more source

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck, Samuel Yanes, Manuel Perales, Daniel Gutiérrez, Sergio Toral   +4 more
wiley   +1 more source

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez, Estefania Ascencio, Jose M. Ageitos, Lucia Feijoo, Shan He, Amirreza Daghighi, Gerardo M. Casanola‐Martin, Cristian R. Munteanu, Santiago Rodriguez Yañez, Alejandro Pazos, Harbil Bediaga, Brenda Durand Ordiales, Raquel Esteban, Ana‐Maria Heres, Jorge Curiel Yuste, Lur Epelde, Bakhtiyor Rasulev, Tomas Gonzalez, Sonia Arrasate, Humberto González‐Diaz   +19 more
wiley   +1 more source

ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH

Informatika, 2016
An on-line unsupervised algorithm for estimating the hidden Markov models (HMM) parame-ters is presented. The problem of hidden Markov models adaptation to emotional speech is solved.
A. V. Tkachenia
doaj  

Emirati-Accented Speaker Identification in each of Neutral and Shouted Talking Environments

, 2018
This work is devoted to capturing Emirati-accented speech database (Arabic United Arab Emirates database) in each of neutral and shouted talking environments in order to study and enhance text-independent Emirati-accented speaker identification ...
Bahutair, Mohammed, Nassif, Ali Bou, Shahin, Ismail   +2 more
core   +1 more source

gnSPADE: Incorporating Gene Network Structures Enhances Reference‐Free Deconvolution in Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
gnSPADE integrates gene‐network structures into a probabilistic topic modeling framework to achieve reference‐free cell‐type deconvolution in spatial transcriptomics. By embedding gene connectivity within the generative process, gnSPADE enhances biological interpretability and accuracy across simulated and real datasets, revealing spatial organization ...
Aoqi Xie, Yuehua Cui
wiley   +1 more source

Analysis of multimodal Bayesian nonparametric autoregressive hidden Markov models for process monitoring in robotic contact tasks

International Journal of Advanced Robotic Systems, 2019
Robot introspection aids robots to understand what they do and how they do it. Previous robot introspection techniques have often used parametric hidden Markov models or supervised learning techniques, implying that the number of hidden states or classes
Hongmin Wu, Yisheng Guan, Juan Rojas
doaj   +1 more source

HIPPI: highly accurate protein family classification with ensembles of HMMs

BMC Genomics, 2016
Background Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance ...
Nam-phuong Nguyen, Michael Nute, Siavash Mirarab, Tandy Warnow   +3 more
doaj   +1 more source

Gene Hunting with Knockoffs for Hidden Markov Models

, 2017
Modern scientific studies often require the identification of a subset of relevant explanatory variables, in the attempt to understand an interesting phenomenon. Several statistical methods have been developed to automate this task, but only recently has
Candès, Emmanuel J., Sabatti, Chiara, Sesia, Matteo   +2 more
core   +1 more source

Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions

Advanced Intelligent Systems, EarlyView.
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li, Yingqian Xu, Caihua Wan, Ran Zhang, Meike Hindenberg, Raik Hoffmann, Shiqiang Liu, Tianyi Zhang, Shilong Xiong, Dehao Kong, Jihao Xia, Fangshuo Gao, Zhuyang Nie, Thomas Kämpfe, Guoqiang Yu, Xiufeng Han   +15 more
wiley   +1 more source