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  1. 1981
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    Anodal Transcranial Direct Current Stimulation Increases Bilateral Directed Brain Connectivity during Motor-Imagery Based Brain-Computer Interface Control
  2. 1982
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    Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery
  3. 1983
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    New Automatized Method of 3D Multiculture Viability Analysis Based on Confocal Imagery: Application to Islets and Mesenchymal Stem Cells Co-Encapsulation
  4. 1984
    “…Changes in noticing, believability and discussions varied somewhat by imagery type across countries. CONCLUSIONS: The different PHW imagery appears to have different pathways of influence on adult smokers. …”
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    Which type of tobacco product warning imagery is more effective and sustainable over time? A longitudinal assessment of smokers in Canada, Australia and Mexico
  5. 1985
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    Modification of 6SV to remove skylight reflected at the air-water interface: Application to atmospheric correction of Landsat 8 OLI imagery in inland waters
  6. 1986
    “…Video data was clearly superior to the still imagery, with more than twice as many burrow occupancies being positively identified (still: 43%). …”
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    A Comparison between Video and Still Imagery as a Methodology to Determine Southern Hairy-Nosed Wombat (Lasiorhinus latifrons) Burrow Occupancy Rates
  7. 1987
    por Dickerson, Kathryn C.
    Publicado 2018
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    Upregulating brain activity using non-drug reward imagery and real-time fMRI neurofeedback–A new treatment approach for addiction?
  8. 1988
    “…We present a high-throughput model-assisted method for characterizing GLAI dynamics in maize (Zea mays subsp. mays) using multispectral imagery acquired from an Unmanned Aerial Vehicle (UAV). …”
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    A High-Throughput Model-Assisted Method for Phenotyping Maize Green Leaf Area Index Dynamics Using Unmanned Aerial Vehicle Imagery
  9. 1989
    “…BACKGROUND: Motor imagery (MI) has been a widely used strategy in the past two decades to enhance physical capabilities among orthopaedic patients. …”
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    Specific and general adaptations following motor imagery practice focused on muscle strength in total knee arthroplasty rehabilitation: A randomized controlled trial
  10. 1990
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    Influence of traffic accessibility on land use based on Landsat imagery and internet map: A case study of the Pearl River Delta urban agglomeration
  11. 1991
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    A Multi-Target Motor Imagery Training Using Bimodal EEG-fMRI Neurofeedback: A Pilot Study in Chronic Stroke Patients
  12. 1992
    “…This paper presents a novel integration of covariate shift estimation and unsupervised adaptive ensemble learning (CSE-UAEL) to tackle non-stationarity in motor-imagery (MI) related EEG classification. The proposed method first employs an exponentially weighted moving average model to detect the covariate shifts in the common spatial pattern features extracted from MI related brain responses. …”
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    Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface
  13. 1993
    “…This study evaluates the potential of high resolution hyperspectral airborne imagery to capture within-field variability of durum wheat grain yield (GY) and grain protein content (GPC) in two commercial fields in the Yaqui Valley (northwestern Mexico). …”
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    Multi-Temporal and Spectral Analysis of High-Resolution Hyperspectral Airborne Imagery for Precision Agriculture: Assessment of Wheat Grain Yield and Grain Protein Content
  14. 1994
    “…This study presents a rapid sensing and yield estimation scheme using off-the-shelf aerial imagery and deep learning. A Region-Convolutional Neural Network was trained to detect and count the number of apple fruit on individual trees located on the orthomosaic built from images taken by the unmanned aerial vehicle (UAV). …”
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    A Cloud-Based Environment for Generating Yield Estimation Maps From Apple Orchards Using UAV Imagery and a Deep Learning Technique
  15. 1995
    “…BACKGROUND: Motor imagery (MI) is effective in improving motor performance in the healthy asymptomatic adult population. …”
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    Home-based motor imagery intervention improves functional performance following total knee arthroplasty in the short term: a randomized controlled trial
  16. 1996
    “…EMG is based on the theoretical tenets of eidetic psychotherapy of Akhter Ahsen, which uses eidetic imagery as its major therapeutic tool. The literature review did not find any empirical study on eidetic imagery-based psychotherapy for people with ID except reviews and case histories. …”
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    Investigating the potential clinical utility of therapeutic techniques based on eidetic imagery as adapted by the Eidetic Model of Growth (EMG) for people with intellectual disability (ID)
  17. 1997
    “…We examined the feasibility of an image-based object-detection analysis approach using very high-spatial-resolution (2.5 m) commercial satellite imagery. We fed the satellite imagery to a deep neural network (DNN) to learn the association between visual urban features and air pollutants. …”
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    A Deep Learning Approach for Meter-Scale Air Quality Estimation in Urban Environments Using Very High-Spatial-Resolution Satellite Imagery
  18. 1998
    “…Motor imagery (MI), i. e., the mental simulation of an action without its actual execution, is a promising technique to boost motor learning via physical practice in rehabilitation, sport, and educational fields. …”
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    Thinking Before Doing: A Pilot Study on the Application of Motor Imagery as a Learning Method During Physical Education Lesson in High School
  19. 1999
    “…In this study, the sources of EEG activity in motor imagery brain–computer interface (BCI) control experiments were investigated. …”
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    Using Multiple Decomposition Methods and Cluster Analysis to Find and Categorize Typical Patterns of EEG Activity in Motor Imagery Brain–Computer Interface Experiments
  20. 2000
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    Quantitative imagery analysis of spot patterns for the three-haplogroup classification of Triatoma dimidiata (Latreille, 1811) (Hemiptera: Reduviidae), an important vector of Chagas disease
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