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 12 of 12 for “"densenet"”.
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Investigation of KimiaNet's and DenseNet's deep features in lung cancer subtypes
Deep neural networks (DNN) have extended applications in the _eld of digital pathology. One of which is to act as feature extractors for content-based image retrieval (CBIR) systems. Therefore, it is necessary to investigate how these deep features work and attribute these features to histologic …
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Single magnetic resonance image super-resolution using generative adversarial network
… Network (GAN) model where the generator has a DenseNet type structure and the discriminator is based on the U-Net model. We have used a combination of loss functions to ensure the generated images are consistent with ground truth. To train and validate the model, we have used four different …
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Network Requirements for Distributed Machine Learning Training in the Cloud
… four popular machine learning models (ResNet, DenseNet, VGG, and BERT) on an Nvidia A-100 cluster to determine the impact of bursty and non-bursty cross traffic (such as web-search traffic and long-lived flows) on the iteration time and throughput of distributed training. By varying the cross …
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Node Classification on Relational Graphs Using Deep-RGCNs
… deep CNN-architectures such as ResNet and DenseNet. In our experiments, we investigate and compare the performance of Deep-RGCN with different baselines on multi-relational graph benchmark datasets, AIFB and MUTAG, and show how the deep architecture boosts the performance in the task of …
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Advancing Precision Agriculture Through AI and Statistical Modeling: Transforming Crop and Livestock Management
… feature extraction methods utilizing ResNet, DenseNet, and ResNeXt are employed to develop ML and deep learning (DL) mod- els, providing a non-invasive alternative to traditional weight measurement techniques. The second part examines the regulation of the auxin response in Arabidopsis plants, …
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Advanced computational techniques for pipe burst detection and localisation in water distribution networks
… achieved a mean accuracy of 98.92% and PSOFL- DenseNet reached 98.78%, significantly outperforming their PBT counterparts at 96.70% and 97.22% respectively.
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Optimizations for Deep Learning-Based CT Image Enhancement
… To that end, we leverage a DL model called DenseNet and Deconvolution Network (DDNet). The model enhances LDCT chest images into high-quality (HQ) ones but requires many hours to train. To further improve the quality of final HQ images, we first modified DDNet's architecture with a more …
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Real-Time Computed Tomography-based Medical Diagnosis Using Deep Learning
… uses a convolution neural network called DenseNet and Deconvolution network (DDnet) to remove noise and artifacts from the input image. To evaluate its advantages in medical diagnosis, we use DDnet to enhance chest CT scans of COVID-19 patients. We show that image enhancement can improve …
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Resource efficient distributed inference of deep neural networks for Edge AI
… 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 efficiency. The integration of asynchronous scheduling, batching, and …
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The Deep Rendering Model: Bridging Theory and Practice in Deep Learning
… the densely connected convolutional networks (DenseNet), providing insights into their successes and shortcomings as well as a principled route to their improvement. The DRMM is also applicable to semi-supervised and unsupervised learning tasks, achieving results that are state-of-the-art in …
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CARAD: Computer-aided Analysis of Radio Astronomy Data
… fewer computational operations than competing DenseNet-based methods. In addition, a content-based image retrieval system is developed using supervised hashing techniques combined with COSFIRE descriptors, enabling efficient similarity searches in large radio galaxy databases with 91% mean …
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ZiZoNet: A Zoom-In and Zoom-Out Mechanism for Crowd Counting in Static Images
As people gather during different social, political or musical events, automated crowd analysis can lead to effective and better management of such events to prevent any unwanted scene as well as avoid political manipulation of crowd numbers. Crowd counting remains an integral part of crowd …