Results 51 to 60 of about 1,512,599 (152)
Vision transformer for reference-based super-resolution
Reference-based Super-Resolution (RefSR) aims to restore a low-resolution image by transferring real textures from a high-resolution reference of similar content, rather than hallucinating missing details as in single-image super-resolution.
A. V. Yakovenko +3 more
doaj +1 more source
RT-ViT: Real-Time Monocular Depth Estimation Using Lightweight Vision Transformers
The latest research in computer vision highlighted the effectiveness of the vision transformers (ViT) in performing several computer vision tasks; they can efficiently understand and process the image globally unlike the convolution which processes the ...
Hatem Ibrahem +2 more
doaj +1 more source
The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive amounts of data using significant computation power.
openaire +1 more source
Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics
Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resources both for training and deployment.
Eyup B. Unlu +10 more
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eolphd/transformer-forecasting: transformer-forecasting
<p>Main code and modules of a transformer neural network for environmental time series forecasting, including input data used for test. Orozco-López and Kaplan "Interpretable Transformer Neural Network Prediction of Diverse Environmental Time ...
eolphd
core +1 more source
Transformer-Based Fusion of Body and Context for Emotion Recognition [PDF]
This paper investigates using image-based features, combining body posture and context, to automatically detect emotions in natural settings. We focus on seven emotions: happy, sad, disgust, neutral, surprise, anger, and fear , from the NCAER dataset. We
Elkorchi Merieme +3 more
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Spiking Convolutional Vision Transformer
This paper introduces the design of a Spiking Convolutional Vision Transformer (SCvT) by using the biological-inspired learning rules including spike-timing-dependent plasticity (STDP) and reward–modulated STDP (R-STDP) for a classification task.
Ekenna, Chinwe +7 more
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Accepted to ECCV2024. Project website: https://jiawei-yang.github.io/DenoisingViT/
Jiawei Yang 0002 +8 more
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The paper develops an efficient computational method for establishing equivalent characteristics of magnetic joints of transformer cores, with special emphasis on step-lap design.
N. Nihat +7 more
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Efficient waste management is crucial for urban environments to maintain cleanliness, reduce environmental impact, and optimize resource allocation. Traditional waste collection systems often rely on scheduled pickups or manual inspections, leading to ...
Parakram Singh Tanwer +4 more
doaj +1 more source

