Results 71 to 80 of about 63,948 (252)
Journal of Field Robotics, EarlyView.ABSTRACT We present a comprehensive teleoperation framework for electric vehicle (EV) battery cell handling, integrating haptic feedback, extended reality (XR) visualization, and task‐parameterized Gaussian mixture regression (TP‐GMR) for adaptive, real‐time trajectory generation.
Alireza Rastegarpanah +5 more
wiley +1 more source
Design of Abnormal Heart Sound Recognition System Based on HSMM and Deep Neural Network
Medical Devices: Evidence and Research, 2022 Hai Yin,1 Qiliang Ma,2 Junwei Zhuang,1 Wei Yu,1 Zhongyou Wang3 1School of Biomedical Engineering and Medical Imaging, Xianning Medical College, Hubei University of Science and Technology, Xianning, 437100, People’s Republic of China; 2School of ...
Yin H, Ma Q, Zhuang J, Yu W, Wang Z
doaj
Neuron's eye view: Inferring features of complex stimuli from neural responses. [PDF]
PLoS Computational Biology, 2017 Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that ...
Xin Chen, Jeffrey M Beck, John M Pearson
doaj +1 more source
Uncovering hidden resting state dynamics: A new perspective on auditory verbal hallucinations
NeuroImage, 2022 In the absence of sensory stimulation, the brain transits between distinct functional networks. Network dynamics such as transition patterns and the time the brain stays in each network link to cognition and behavior and are subject to much investigation.
Hanna Honcamp +4 more
doaj +1 more source
Human activity learning and segmentation using partially hidden discriminative models [PDF]
, 2005 Learning and understanding the typical patterns in the daily activities and routines of people from low-level sensory data is an important problem in many application domains such as building smart environments, or providing intelligent assistance ...
Bui, Hung H. +2 more
core
hsmm — An R package for analyzing hidden semi-Markov models
Computational Statistics & Data Analysis, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bulla, Jan, Bulla, Ingo, Nenadic, Oleg
openaire +3 more sources
Journal of Field Robotics, EarlyView.ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong +13 more
wiley +1 more source
Explicit Modeling of Brain State Duration Using Hidden Semi Markov Models in EEG Data
IEEE AccessWe consider the detection and characterization of brain state transitions based on ongoing electroencephalography (EEG). Here, a brain state represents a specific brain dynamical regime or mode of operation that produces a characteristic quasi-stable ...
Nelson J. Trujillo-Barreto +3 more
doaj +1 more source
International Journal of Distributed Sensor Networks, 2013 Most of analyses for the IEEE 802.15.4 Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) scheme for multi-hop wireless sensor networks (WSNs) focus on how to avoid the impacts of hidden terminal problems rather than how to derive the exact
Jianping Zhu, Chunfeng Lv, Zhengsu Tao
doaj +1 more source
Semi-Supervised Learning of Hidden Markov Models via a Homotopy Method [PDF]
, 2006 Hidden Markov model (HMM) classifier design is considered for analysis of sequential data, incorporating both labeled and unlabeled data for training; the balance between labeled and unlabeled data is controlled by an allocation parameter lambda in [0, 1)
Carin, Lawrence +2 more
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