Results 221 to 230 of about 117,002 (264)

Directional Latent Hybridization: Beyond Random Noise in Physics‐Informed Generative Inverse Design of Nonlinear Metamaterials

open access: yesAdvanced Materials Technologies, EarlyView.
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn   +2 more
wiley   +1 more source

Flexible Tactile Actuator Arrays With Integrated Electroosmotic Pumps for Wearable Haptic Systems

open access: yesAdvanced Materials Technologies, EarlyView.
1 ×$\times$ 9 and 4 ×$\times$ 4 flexible tactile actuator arrays integrating electroosmotic pumps are developed to deliver pressure and vibration feedback on wearable platforms. Their thin, compliant structure conforms seamlessly to curved body surfaces, providing intimate contact and enhanced haptic sensations.
Heejin Yu, Joonbum Bae
wiley   +1 more source

Correction: Star Generative Adversarial VGG Network-Based Sample Augmentation for Insulator Defect Detection

open access: yesInternational Journal of Computational Intelligence Systems
Linghao Zhang   +5 more
doaj   +1 more source

Evaluation of the Effectiveness of the Socket Preservation Technique Using Allogeneic and Xenogeneic Materials: A Randomized Controlled Trial. [PDF]

open access: yesJ Funct Biomater
Wróbel P   +11 more
europepmc   +1 more source

Biological Augmentation of Reamed Intramedullary Nailing for Aseptic Tibial Shaft Nonunion: An Exploratory Multicenter Retrospective Comparative Cohort Study. [PDF]

open access: yesJ Funct Morphol Kinesiol
Coviello M   +11 more
europepmc   +1 more source
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Learning Sample-Specific Policies for Sequential Image Augmentation

Proceedings of the 29th ACM International Conference on Multimedia, 2021
This paper presents a policy-driven sequential image augmentation approach for image-related tasks. Our approach applies a sequence of image transformations (e.g., translation, rotation) over a training image, one transformation at a time, with the augmented image from the previous time step treated as the input for the next transformation.
Pu Li, Xiaobai Liu, Xiaohui Xie
openaire   +1 more source

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