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Imágenes (Psicología)
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1221“…Motor imagery (MI) refers to the mental rehearsal of movement in the absence of overt motor action, which can activate or inhibit cortical excitability. …”
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1222por Ji, Yishan, Chen, Zhen, Cheng, Qian, Liu, Rong, Li, Mengwei, Yan, Xin, Li, Guan, Wang, Dong, Fu, Li, Ma, Yu, Jin, Xiuliang, Zong, Xuxiao, Yang, Tao“…CONCLUSION: The results of this study indicated that it is feasible to monitor the plant height of faba bean during the whole growth period based on UAV imagery. Furthermore, the machine learning algorithms can estimate the yield of faba bean reasonably with the multiple time points data of plant height. …”
Publicado 2022
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1223
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1224“…With the development of technology and the rise of the meta-universe concept, the brain-computer interface (BCI) has become a hotspot in the research field, and the BCI based on motor imagery (MI) EEG has been widely concerned. However, in the process of MI-EEG decoding, the performance of the decoding model needs to be improved. …”
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1225“…Clinical trials assessing the effect of graded motor imagery (GMI) in FS are lacking. The aim of this study was to determine the effect of GMI as an adjunct to conventional physiotherapy in individuals with painful FS. …”
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1226Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learningpor Bellis, Emily S., Hashem, Ahmed A., Causey, Jason L., Runkle, Benjamin R. K., Moreno-García, Beatriz, Burns, Brayden W., Green, V. Steven, Burcham, Timothy N., Reba, Michele L., Huang, Xiuzhen“…Unmanned aerial vehicles (UAVs) equipped with multispectral sensors offer high spatial and temporal resolution imagery for monitoring crop stress at early stages of development. …”
Publicado 2022
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1227“…BACKGROUND: Motor Imagery (MI) Brain Computer Interface (BCI) directly links central nervous system to a computer or a device. …”
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1228“…To date, the best technique for the treatment of traumatic sleep disturbances seems to be Imagery Rehearsal Therapy (IRT), an empirically supported method. …”
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1229“…Significant variation in performance in motor imagery (MI) tasks impedes their wide adoption for brain-computer interface (BCI) applications. …”
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1231por Suica, Zorica, Behrendt, Frank, Gäumann, Szabina, Gerth, Ulrich, Schmidt-Trucksäss, Arno, Ettlin, Thierry, Schuster-Amft, Corina“…BACKGROUND: Over the last two centuries, researchers developed several assessments to evaluate the multidimensional construct of imagery. However, no comprehensive systematic review (SR) exists for imagery ability evaluation methods and an in-depth quality evaluation of their psychometric properties. …”
Publicado 2022
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1232por Peterson, Victoria, Galván, Catalina, Hernández, Hugo, Saavedra, María Paula, Spies, Ruben“…These data provide a motor imagery vs. rest EEG dataset, relevant for BCI for motor rehabilitation applications. …”
Publicado 2022
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1233por de Souza, Rafaela Faustino Lacerda, Mendes, Thatiane Maria Almeida Silveira, Lima, Luana Adalice Borges de Araujo, Brandão, Daniel Soares, Laplagne, Diego Andrés, de Sousa, Maria Bernardete Cordeiro“…Mu is a sensorimotor rhythm observed by electroencephalography (EEG) in alpha (8–12 Hz) and beta (15–30 Hz) frequency bands in practices such as motor imagery (MI) and action observation (AO). This rhythm represents a window for studying the activity of neural circuits involved in motor cognition. …”
Publicado 2022
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1234por Wang, Fan, Liu, Huadong, Zhao, Lei, Su, Lei, Zhou, Jianhua, Gong, Anmin, Fu, Yunfa“…Common spatial pattern (CSP) is an effective algorithm for extracting electroencephalogram (EEG) features of motor imagery (MI); however, CSP mainly aims at multichannel EEG signals, and its effect in extracting EEG features with fewer channels is poor—even worse than before using CSP. …”
Publicado 2022
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1235An approach to fill in missing data from satellite imagery using data-intensive computing and DINEOFpor Lomelí-Huerta, José Roberto, Rivera-Caicedo, Juan Pablo, De-la-Torre, Miguel, Acevedo-Juárez, Brenda, Cepeda-Morales, Jushiro, Avila-George, Himer“…The proposed approach merges satellite imagery from diverse sources to reduce the impact of the holes in images that result from acquisition conditions: occlusion, the satellite trajectory, sunlight, among others. …”
Publicado 2022
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1236“…The goal of this study is to develop both fully supervised and weakly supervised deep learning models to segment and count cotton bolls from proximal imagery. A total of 290 RGB images of cotton plants from both potted (indoor and outdoor) and in-field settings were taken by consumer-grade cameras and the raw images were divided into 4350 image tiles for further model training and testing. …”
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1237“…We found that films with computer-generated imagery (CGI) primates were more likely to have higher profits and critic scores. …”
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1240por Zhou, Xin-Xing, Li, Yang-Yang, Luo, Yuan-Kai, Sun, Ya-Wei, Su, Yi-Jun, Tan, Chang-Wei, Liu, Ya-Ju“…This method could be applied to remote sensing classification of fruit trees in a large area, and could provide effective technical means for monitoring fruit tree planting areas with medium and high resolution remote sensing imageries.…”
Publicado 2022
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