Results 31 to 40 of about 325,176 (282)
Sensors, 2022 Aiming at the problems of low fault diagnosis accuracy caused by insufficient samples and unbalanced data sample distribution in bearing fault diagnosis, this paper proposes a fault diagnosis method for rolling bearings referencing conditional deep ...
Cheng Peng, Shuting Zhang, Changyun Li
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FMix: Enhancing Mixed Sample Data Augmentation
, 2020 Code available at https://github.com/ecs-vlc ...
Harris, Ethan +5 more
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Augmenting sampling based controllers with machine learning [PDF]
Proceedings of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 2017 Efficient learning of 3D character control still remains an open problem despite of the remarkable recent advances in the field. We propose a new algorithm that combines planning by a sampling-based model-predictive controller and learning from the planned control, which is very noisy.
Hämäläinen, Perttu, Rajamäki, Joose
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Smart Augmentation - Learning an Optimal Data Augmentation Strategy [PDF]
, 2017 A recurring problem faced when training neural networks is that there is typically not enough data to maximize the generalization capability of deep neural networks(DNN).
Bazrafkan, Shabab +2 more
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Remote Sensing Target Tracking in UAV Aerial Video Based on Saliency Enhanced MDnet
IEEE Access, 2019 Remote sensing target tracking in the aerial video from unmanned aerial vehicles (UAV) plays a key role in public security. As the UAV aerial video has rapid changes in scale and perspective, few pixels in the target region, and multiple similar ...
Fukun Bi +3 more
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Cotton Fusarium wilt diagnosis based on generative adversarial networks in small samples
Frontiers in Plant Science, 2023 This study aimed to explore the feasibility of applying Generative Adversarial Networks (GANs) for the diagnosis of Verticillium wilt disease in cotton and compared it with traditional data augmentation methods and transfer learning. By designing a model
Zhenghang Zhang +12 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingCollaborative representation (CR) models have been widely used in hyperspectral image (HSI) classification tasks. However, most CR classification models lack stability and generalization when targeting small samples as well as spatial homogeneity and ...
Hongjun Su +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe remote sensing mapping of paddy rice in Southwest China faces challenges such as fragmented parcels and difficulties in field sample collection, hindering deep learning technology applications. To address sample scarcity for deep learning-based paddy
Ziyi Tang +5 more
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Discounting and Augmentation of Dispositional and Causal Attributions
Psychologica Belgica, 2006 This article investigates whether and how discounting and augmentation of dispositional and causal attributions differ between each other. In three experiments, the strength of a causal or dispositional attribution to a target actor (or object) was ...
Frank Van Overwalle
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Sample Efficiency of Data Augmentation Consistency Regularization
, 2022 Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data. In this paper, we take a step in this direction - we first present a simple and novel analysis for linear regression with label invariant augmentations ...
Yang, Shuo +5 more
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