Results 161 to 170 of about 511,753 (356)

Speech Synthesis Based on Hidden Markov Models [PDF]

, 2013
Nankaku, Y., Oura, K., Toda, T., Tokuda, K., Yamagishi, J., Zen, H.   +5 more
core   +1 more source

Robotic Cell Micromanipulation Skill Learning via Imitation‐Enhanced Reinforcement Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Humans can learn complex and dexterous manipulation tasks by observing videos, imitating and exploring. Multiple end‐effectors manipulation of free micron‐sized deformable cells is one of the challenging tasks in robotic micromanipulation. We propose an imitation‐enhanced reinforcement learning method inspired by the human learning process ...
Youchao Zhang, Fanghao Wang, Xiangyu Guo, Yibin Ying, Mingchuan Zhou, Zhongliang Jiang, Alois Knoll   +6 more
wiley   +1 more source

Analysis of nanopore data using hidden Markov models [PDF]

, 2015
Jacob Schreiber, Kevin Karplus
openalex   +1 more source

Penerapan Hidden Markov Model (HMM) dan Mel-Frequency Cesptral Coefficients (MFCC) pada E-Learning Bahasa Madura untuk Anak Usia Dini [PDF]

, 2020
Ubaidi Ubaidi, Nindian Puspa Dewi
openalex   +1 more source

Liver Disease Recognition: A Discrete Hidden Markov Model Approach [PDF]

, 2016
Farzan Madadizadeh, Mohamad Ezati Asar, Abbas Bahrampour, Mitra Montazeri   +3 more
openalex  

The shibirets4 mutation causes temperature sensitive paralytic and lethal phenotypes in the Queensland fruit fly, Bactrocera tryoni

Insect Science, EarlyView.
Abstract Bactrocera tryoni, the Queensland fruit fly, is among the most damaging insect pests to the Australian horticultural industry as larvae infest ripening fruits or vegetables prior to harvest. Genetic biocontrol using Sterile Insect Technique (SIT) programs have been used to successfully suppress populations, via mass release of factory‐reared ...
Anzu Okada, Mamoru Okamoto, Thu N.M. Nguyen, Elisabeth Fung, Han Nguyen, Peter Crisp, Amanda Choo, Simon W. Baxter   +7 more
wiley   +1 more source

Infinite hidden Markov models can dissect the complexities of learning. [PDF]

Nat Neurosci
Bruijns SA, International Brain Laboratory, Bougrova K, Laranjeira IC, Lau PYP, Meijer GT, Miska NJ, Noel JP, Pan-Vazquez A, Roth N, Socha KZ, Urai AE, Dayan P.   +12 more
europepmc   +1 more source

Hidden Markov models for presence detection based on CO₂ fluctuations. [PDF]

Front Robot AI, 2023
Karasoulas C, Keroglou C, Katsiri E, Sirakoulis GC.   +3 more
europepmc   +1 more source

Chromosome‐scale genome assembly of the South American fruit fly, Anastrepha fraterculus sp.1

Insect Science, EarlyView.
Anastrepha fraterculus sp. 1 is a major fruit fly pest in Argentina, currently controlled through chemical treatments and traps. This study aims to enhance the genomic understanding of this species to support the development of sterile insect technique as well as the use of innovative technologies.
Máximo Rivarola, Claudia A. Conte, Pierre Berube, Shu‐Huang Chen, M. Cecilia Giardini, Alejandra C. Scannapieco, Fabián H. Milla, María C. Soria, Romina M. Russo, Juan P. Wulff, Haig H. Djambazian, Rolando R. Pomar, Alfred M. Handler, Kostas Bourtzis, Ioannis Ragoussis, Silvia B. Lanzavecchia   +15 more
wiley   +1 more source

Evidence for mood instability in patients with bipolar disorder: Applying multilevel hidden Markov modeling to intensive longitudinal ecological momentary assessment data.

Sebastian Mildiner Moraga, Fionneke M. Bos, Bennard Doornbos, Richard Bruggeman, Lian van der Krieke, Evelien Snippe, Emmeke Aarts   +6 more
openalex   +2 more sources