Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"Vision Transformer (ViT)"”.
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Thermodynamics of 5-flavor QCD
… the Masked Autoregressive Flow (MAF) and the Vision Transformer (ViT) to QCD data analysis. This approach is used to identify a critical mass marking the boundary between first-order and crossover regions. Another part of this thesis analyzes scaling functions in the 3-d, Z(2), O(2) and O(4) …
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VADViT:Vision Transformer-Driven Memory Forensics for Malicious Process Detection and Explainable Threat Attribution
… To address these challenges, we propose VADViT, a vision-based transformer model that detects malicious processes by analyzing Virtual Address Descriptor (VAD) memory regions. VADViT converts these structures into Markov, entropy, and intensity-based images, classifying them using a Vision …
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Estimating diurnal patterns of land surface temperature using vision transformers and satellite images
… such as climatic zones and elevation. Built on a Vision Transformer (ViT) architecture with a Masked Autoencoder strategy, DayView directly addresses three core challenges: (1) estimating diurnal cycles from sparse observations, (2) incorporating environmental context to refine fluctuation …
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A Novel Approach to Indoor Environment Assessment: Artificial Intelligence of Things (AIoT) Framework for Improving Occupant Comfort and Health in Educational Facilities
… recordings, video/thermal features extracted by Vision Transformer (ViT)), and self-reported comfort and health levels, placing a focus on occupant-centric and data-driven decision-making for intelligent educational facilities. The proposed framework was evaluated and validated at Virginia Tech …
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Searching for Efficient Multi-Stage Vision Transformers
Vision Transformer (ViT) demonstrates that Transformer for natural language processing can be applied to image classification tasks and result in comparable performance to convolutional neural networks (CNN), which have been studied in computer vision for years. This naturally raises the question …
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Resource efficient distributed inference of deep neural networks for Edge AI
… experiments are conducted using advanced vision architectures such as Vision Transformer (ViT), Swin Transformer, DenseNet, and ResNet under diverse deployment scenarios. Results demonstrate up to 67% reduction in total inference time, alongside improvements in GPU utilization and energy …
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IntelliEdgent: device-server collaborative deep learning model composition for resource-efficient edge intelligence
… Thirdly, we study a device-server collaborative Vision Transformer (ViT) classifier called FactionFormer, based on the idea of a dynamically changing narrower deployment context compared to the off-the-shelf pretrained classifier. Besides these three works, we have other two works in the pipeline …
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Advancing Automatic Brain Tumour Segmentation Using Multi-Modal MRI
… on MRIs, based on the state-of-the-art vision transformer (ViT) with a modified convolutional neural network (CNN) encoder. Evaluated on the BraTS 2021 dataset, 3D CATBraTS achieved quantitative measures that surpassed the current state-of-the-art approaches. We further introduce …
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A Multi-head Attention Approach with Complementary Multimodal Fusion for Vehicle Detection
… of sophisticated sensor fusion techniques as vital tools in overcoming the challenges posed by adverse environmental conditions, thus paving the way for more resilient and reliable autonomous vehicular technologies.