Results 41 to 50 of about 83,465 (280)
Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods [PDF]
, 2018 This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises ...
Arcos García, Álvaro +2 more
core +1 more source
The Multiscale Surface Vision Transformer
ArXiv, 2023 Accepted for publication at MIDL 2024, 17 pages, 6 ...
Dahan, Simon +3 more
openaire +3 more sources
Variable-Rate Deep Image Compression With Vision Transformers
IEEE Access, 2022 Recently, vision transformers have been applied in many computer vision problems due to its long-range learning ability. However, it has not been throughly explored in image compression.
Binglin Li, Jie Liang, Jingning Han
doaj +1 more source
, 2022 Human vision possesses a special type of visual processing systems called peripheral vision. Partitioning the entire visual field into multiple contour regions based on the distance to the center of our gaze, the peripheral vision provides us the ability to perceive various visual features at different regions.
Min, Juhong +3 more
openaire +2 more sources
EnViTSA: Ensemble of Vision Transformer with SpecAugment for Acoustic Event Classification
Sensors, 2023 Recent successes in deep learning have inspired researchers to apply deep neural networks to Acoustic Event Classification (AEC). While deep learning methods can train effective AEC models, they are susceptible to overfitting due to the models’ high ...
Kian Ming Lim +3 more
doaj +1 more source
Through-Ice Acoustic Source Tracking Using Vision Transformers with Ordinal Classification
Sensors, 2022 Ice environments pose challenges for conventional underwater acoustic localization techniques due to their multipath and non-linear nature. In this paper, we compare different deep learning networks, such as Transformers, Convolutional Neural Networks ...
Steven Whitaker +3 more
doaj +1 more source
Language Modeling with Deep Transformers
, 2019 We explore deep autoregressive Transformer models in language modeling for speech recognition. We focus on two aspects. First, we revisit Transformer model configurations specifically for language modeling. We show that well configured Transformer models
Irie, Kazuki +3 more
core +1 more source
Art authentication with vision transformers
Neural Computing and Applications, 2023 AbstractIn recent years, transformers, initially developed for language, have been successfully applied to visual tasks. Vision transformers have been shown to push the state of the art in a wide range of tasks, including image classification, object detection, and semantic segmentation.
Schaerf, Ludovica +2 more
openaire +3 more sources
Visual Recovery Reflects Cortical MeCP2 Sensitivity in Rett Syndrome
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Rett syndrome (RTT) is a devastating neurodevelopmental disorder with developmental regression affecting motor, sensory, and cognitive functions. Sensory disruptions contribute to the complex behavioral and cognitive difficulties and represent an important target for therapeutic interventions.
Alex Joseph Simon +12 more
wiley +1 more source
Permeability Prediction Using Vision Transformers
Mathematical and Computational ApplicationsAccurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields.
Cenk Temizel +5 more
doaj +1 more source