Results 271 to 280 of about 72,528 (341)

Experiment study on UAV target detection algorithm based on YOLOv8n-ACW. [PDF]

Sci Rep
Xue B, Zhang B, Cheng Q.
europepmc   +1 more source

Artificial intelligence in mitotic checkpoint modeling: transforming our understanding of cellular division through machine learning and predictive biology. [PDF]

Brief Bioinform
Ibrahim B.
europepmc   +1 more source

Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics. [PDF]

Brief Bioinform
Hu Y, Xiao K, Yang H, Liu X, Zhang C, Shi Q.   +5 more
europepmc   +1 more source

"Desired behaviors": alignment and the emergence of a machine learning ethics. [PDF]

AI Soc
Schwerzmann K, Campolo A.
europepmc   +1 more source

The feeling of exclusion and/or inclusion in shared places: Syrian students' emotions and social imaginations in Istanbul. [PDF]

Heliyon
Ayyildiz Ş.
europepmc   +1 more source

Embodied engagement: fostering caring thinking in a multimodal singing-based learning environment for refugee children. [PDF]

Front Psychol
Mohammadhosseini M, Schmid S.
europepmc   +1 more source

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CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders

Neural Information Processing Systems, 2023
A vital and rapidly growing application, remote sensing offers vast yet sparsely labeled, spatially aligned multimodal data; this makes self-supervised learning algorithms invaluable.
A. Fuller, K. Millard, James R. Green
semanticscholar   +1 more source

Enhancing Multiscale Representations With Transformer for Remote Sensing Image Semantic Segmentation

IEEE Transactions on Geoscience and Remote Sensing, 2023
Semantic segmentation is an extremely challenging task in high-resolution remote sensing (HRRS) images as objects have complex spatial layouts and enormous variations in appearance.
Tao Xiao, Yikun Liu, Yuwen Huang, Mingsong Li, Gongping Yang   +4 more
semanticscholar   +1 more source

Geometric deep learning on molecular representations

Nature Machine Intelligence, 2021
Geometric deep learning (GDL) is based on neural network architectures that incorporate and process symmetry information. GDL bears promise for molecular modelling applications that rely on molecular representations with different symmetry properties and
Kenneth Atz, F. Grisoni, G. Schneider
semanticscholar   +1 more source

Spatial Representation of Maps

The American Journal of Psychology, 1983
Two experiments tested the hypothesis that the cognitive representation of spatial relations on a map is primarily a visually keyed process. In Experiment 1, undergraduates studied a labeled map where features were presented either as words alone, as mimetic drawings of the referent, or as geometric symbols.
R W, Kulhavy, N H, Schwartz, S H, Shaha
openaire   +2 more sources