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  1. 961
    por You, Hojun, Kim, Dongsu
    Publicado 2021
    “…Furthermore, the spatial accuracy of this technique needs to be verified, as it has not been widely applied to hyperspectral imagery. The proposed technique resulted in an average reduction of spatial errors by 91.9%, compared to the case where the image registration technique was not applied, and by 78.7% compared to template matching.…”
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    Development of an Image Registration Technique for Fluvial Hyperspectral Imagery Using an Optical Flow Algorithm
  2. 962
    “…Motor imagery is defined as an act wherein an individual contemplates a mental action of motor execution without apparent action. …”
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    Comparison of cerebral activation between motor execution and motor imagery of self-feeding activity
  3. 963
    “…During the summer of 2017, an airborne flight campaign acquired mid-wave infrared imagery over active wildfires in Northern Ontario, Canada. …”
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    Geocorrection of Airborne Mid-Wave Infrared Imagery for Mapping Wildfires without GPS or IMU
  4. 964
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    Using satellite imagery to evaluate precontact Aboriginal foraging habitats in the Australian Western Desert
  5. 965
    “…Visual experiences can be triggered externally, by signals coming from the outside world during perception; or internally, by signals from memory during mental imagery. Imagery and perception activate similar neural codes in sensory areas, suggesting that they might sometimes be confused. …”
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    Mistaking imagination for reality: Congruent mental imagery leads to more liberal perceptual detection
  6. 966
    “…OBJECTIVES: Though exposure to alcohol imagery in films is a significant determinant of uptake and severity of alcohol consumption among young people, there is poor evidence regarding the content of alcohol imagery in films in low-income and middle-income countries. …”
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    Quantifying audio visual alcohol imagery in popular Indian films: a content analysis
  7. 967
    “…Satellite imagery is changing the way we understand and predict economic activity in the world. …”
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    Deep learning-based object recognition in multispectral satellite imagery for real-time applications
  8. 968
    “…Here, we proposed an updated paradigm utilizing motor coordination imagery involving the lower limbs (normal gait imagery and hemiplegic gait imagery after stroke) and decoded such imagery via an electroencephalogram- (EEG-) based brain network. …”
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    Decoding of Motor Coordination Imagery Involving the Lower Limbs by the EEG-Based Brain Network
  9. 969
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    Qualification of Soybean Responses to Flooding Stress Using UAV-Based Imagery and Deep Learning
  10. 970
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    Author Correction: In your phase: neural phase synchronisation underlies visual imagery of faces
  11. 971
    “…The results highlight music’s potential to support therapies such as Exposure Therapy and Imagery Rescripting, which deploy directed imagination as a clinical tool.…”
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    Music influences vividness and content of imagined journeys in a directed visual imagery task
  12. 972
    “…OBJECTIVE: This research investigated these active, imagery and passive movements in volunteers design to permit a comparison of their capabilities in activating the brain areas. …”
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    Assessment of Motor Cortex in Active, Passive and Imagery Wrist Movement Using Functional MRI
  13. 973
    “…In this study, we investigate the potential for achieving better subject-independent motor imagery BCI performance by conducting comparative performance tests with several selective subject pooling strategies (i.e., choosing subjects who yield reasonable performance selectively and using them for training) rather than using all subjects available. …”
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    Selective Subject Pooling Strategy to Improve Model Generalization for a Motor Imagery BCI †
  14. 974
    “…In this study, we conducted a seven-session motor-imagery (MI) experiment on 20 healthy subjects to investigate the neurophysiological mechanism on the performance variation. …”
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    Relative Power Correlates With the Decoding Performance of Motor Imagery Both Across Time and Subjects
  15. 975
    “…Motor imagery (MI)-based brain–computer interfaces have gained much attention in the last few years. …”
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    Effective Connectivity for Decoding Electroencephalographic Motor Imagery Using a Probabilistic Neural Network
  16. 976
    por Huang, Xiuyu, Zhou, Nan, Choi, Kup-Sze
    Publicado 2021
    “…Convolutional neural networks (CNNs) have been widely applied to the motor imagery (MI) classification field, significantly improving the state-of-the-art (SoA) performance in terms of classification accuracy. …”
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    A Generalizable and Discriminative Learning Method for Deep EEG-Based Motor Imagery Classification
  17. 977
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    Detecting Plant Stress Using Thermal and Optical Imagery From an Unoccupied Aerial Vehicle
  18. 978
    “…In this context, a novel method is devised for automated identification of the Motor Imagery (MI) tasks. The contribution is an effective hybridization of the Multiscale Principal Component Analysis (MSPCA), Wavelet Packet Decomposition (WPD), statistical features extraction from subbands, and ensemble learning-based classifiers for categorization of the MI tasks. …”
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    The Ensemble Machine Learning-Based Classification of Motor Imagery Tasks in Brain-Computer Interface
  19. 979
    “…BACKGROUND: A growing body of evidence suggests the benefit of motor imagery in motor learning. While some studies tried to look at the effect of isolated mental practice, others evaluated the combined effect of motor imagery and physical practice in clinical rehabilitation. …”
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    Effects of task complexity or rate of motor imagery on motor learning in healthy young adults
  20. 980
    “…In this study, we analyse the pre- and post-training EEG from 11 elderly subjects who performed an NFT based on motor imagery (MI–NFT). Spectral changes were studied using relative power (RP) from classical frequency bands (delta, theta, alpha, and beta), whilst multiscale entropy (MSE) was applied to assess EEG-induced complexity changes. …”
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    Neurofeedback Training Based on Motor Imagery Strategies Increases EEG Complexity in Elderly Population
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