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.
Results
Showing 1 to 20 of 25 for “"Image translation"”.
-
Meta-Learning and Self-Supervised Pretraining for Few-shot Image Translation
… work and contribute a novel few-shot multi-task image to image translation problem. We then present several benchmarks for this problem using ideas from both meta-learning and contrastive-learning and improve upon baselines trained using simple supervised learning. Additionally, we contribute to …
-
Text-Guided Image-to-Image Translation for Converting RGB Maps to Tactile Images
… tactile maps from RGB maps using text-guided image-to-image translation. By leveraging natural language prompts, the method enables control over map details, such as lakes, rivers, and cities, allowing outputs to be tailored to specific needs. A custom dataset of 1,845 RGB maps was developed, …
-
Learning to map between domains
… something seen before. Similarly, in the medical image field and radiological science, tens of thousands of medical images (MRI, CT, etc) of patients are taken. These medical images need to be studied and interpreted. In this dissertation, we investigate a number of data-driven approaches for …
-
First Principles of Line Drawings
… a set of first principle objectives and train an image translation network to map 3D objects into line drawings. We also explore generation of new styles of line drawings through a novel style confusion loss which averages and combines elements from different styles in a structured manner. User …
-
Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection
… drone detection is the limited amount of drone images for training. To address this issue, we used Generative Adversarial Networks, CycleGAN to be precise, for the generation of realistic looking fake images which were indistinguishable from real data. CycleGAN is a classic example of Image to …
-
Deep Learning Tools for Next-Generation Connectomics
… to reconstruct nanoscale maps of large-scale images, allowing us a better understanding of how neural tissue computes. However, our ability to build powerful tools for the next generation of connectomics is dependent on navigating an inherent accuracy v.s. speed v.s. scalability trade-off. …
-
Multimodal Foundation Models through the Lens of Security: Robust Deepfake Detection and Adversarial Resilience
… process multiple types of data, such as text, images, video as input and output, enabling seamless interaction across different modalities. Examples include Text-to-Image (T2I) generation models like DALL-E and Stable Diffusion, which create highly realistic images from simple text prompts. …
-
Unsupervised Domain Adaptation per la rilevazione di oggetti e riconoscimento di azioni
… basate su adversarial learning, self-training e image-to-image translation per apprendere rappresentazioni invarianti rispetto al dominio che possono generalizzare su singoli o multipli domini di destinazione. Per il riconoscimento delle azioni, analizziamo la capacità dei metodi più avanzati …
-
Algorithms for robust autonomous navigation in human environments
… the contextual scene understanding problem as an image translation problem, by learning to estimate the planning cost-to-go from aerial images of similar environments. The proposed perception algorithm is united with a motion planner to reduce the amount of exploration time before finding the …
-
Representations for intelligent navigation in unfamiliar environments
… cost. Second, we apply recent progress in image-to-image translation to the task of domain adaptation for image data, allowing an agent to transfer knowledge acquired in simulation to the real world. Finally, we introduce a learned pseudosensor and accompanying probabilistic sensor model …
-
Deep learning for automatic microscopy image analysis
… techniques allow for the creation of detailed images of cells (or nuclei) and have been widely employed for cell studies in biological research and disease diagnosis in clinic practices.Microscopy image analysis (MIA), with tasks of cell detection, cell classification, and cell counting, etc., …
-
Robustifying Machine Learning based Security Applications
… First, we start from adversarial examples in image recognition. We develop a method to generate robust adversarial examples that remain effective in the physical domain. Our core idea is to use an image-to-image translation network to simulate the digital-to-physical transformation process for …
-
Enhancing dimensionality in remote sensing images
… surface. These modalities include panchromatic images, which are single-band grayscale representations; multispectral images, capturing a limited number of spectral bands; and hyperspectral images, encompassing a broad spectrum with numerous spectral bands. Images of the same scene are often …
-
Towards Learning the Geometry of Data: From Diffusion Models to Riemannian Geometry
… a conditional normalising flow that improves image-to-image translation by hierarchically modelling image distributions across scales. In chapter 4, we introduce non-uniform diffusion models, which apply faster diffusion speed to high-frequency information and slower diffusion speed to …
-
Generative Adversarial Network (GAN) for Medical Image Synthesis and Augmentation
Medical image processing aided by artificial intelligence (AI) and machine learning (ML) significantly improves medical diagnosis and decision making. However, the difficulty to access well-annotated medical images becomes one of the main constraints on further improving this technology. Generative …
-
Capsule Networks: Framework and Application to Disentanglement for Generative Models
… of applications in various domains such as image-to-image translation, video prediction, and generating synthetic data where accessing real data is expensive, unethical, or compromising privacy. One of the main challenges in designing a generative model is creating a disentangled …
-
Toward reliable localization: exploring infrared fiducial markers and multi-imu fusion as alternative sensor modalities
… estimation framework based on thermal infrared imagery. In addition, low-cost MEMS IMUs typically used in these systems suffer from high noise and bias instability, limiting the overall accuracy and robustness of the pose estimation. To overcome these challenges, this work proposes two …
-
Dynamic image crowd representations for improved anomaly detection using generative adversarial networks
… information source, some of which contain images of crowds of high density. However, relying on the typical manual surveillance systems for detecting anomalies (any behaviour outlying from established normalcy) in crowds presents complications concerning accuracy and computation power. This …
-
Novel time resolved optical and machine learning methods for label free biomedical imaging
… to the required level so that Fibroblasts can be imaged with sufficient Signal-to-Noise Ratio (SNR). The major technical challenges that had to be overcome to obtain reasonable pump-probe signal levels from fibroblasts are: (1) minimizing the noise floor of the entire optical instrument so that we …
-
Learning to Adapt Neural Networks Across Visual Domains
… to address multi-source DA by posing it as an image translation problem. This proposed framework TriGAN allows a single generator to be learned by using all the source domain data into a single network, leading to better generation of target-like source data. (iii) We address multi-target DA by …
Page 1 of 2