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 26 for “"Temporal Modeling"”.
-
Human-Centric Spatio-temporal Modeling and Analysis for Multimedia Data
… intelligence and deep learning, the spatio-temporal modeling and analysis of multimedia data have ascended to unprecedented importance. My dissertation navigates through the complexities of this domain, particularly emphasizing object analysis and behavior recognition. Here, the accurate and …
-
Using Data Augmentation and Stochastic Differential Equations in Spatio Temporal Modeling
<p>One of the biggest challenges in spatiotemporal modeling is indeed how to manage the large amount of missing information. Data augmentation techniques are frequently used to infer about missing values, unobserved or latent processes, approximation of continuous time processes that are discretely …
-
Spatio-temporal modeling of Louisiana land subsidence using high resolution geo-spatial data
… et al. 1998). Results by KKF have shown spatio-temporal distributions of subsidence rates from 2011 to 2013, and these results have also been validated by the Bayou Corne Sinkhole knowledge in this research (Mardia et al. 1998; Cusanza 2013; Jones and Blom 2014; Jones and Blom 2015). Based on …
-
Multiscale spatio-temporal modeling of cell population in tissue architecture and drug delivery nanoparticles
… and computationally challenging. The multiscale modeling approach can bridge the gap between different scale by a systemic integration of the complex dynamic behavior.</p><p>Here, the focus is on developing multiscale modeling approaches to study the dynamic behavior of tissue. First, a …
-
2-D and 3-D Temporal Modeling of Solute Migration through Low Permeable Media using Electrical Resistivity, Nacogdoches County, Texas
… to characterize solute transport. 2-D and 3-D temporal resistivity data collected with an AGI SuperSting (R8/IP) were processed with AGI Earthimager 2D/3D software for inversion modeling. Data were collected over 135 days within a 14 X 26 meter (46 X 85 feet) gridded survey at 15-day intervals …
-
Dynamic Spatio-Temporal Graph Convolutional Networks
Spatio-temporal modeling is an essential lens to understand many real-world phenomena from traffic [20] [10] to epidemiology [12]. Although forecasting time series is an exceptionally well-studied problem, recent years have seen impressive gains in the performance of graph learning as a paradigm …
-
Spatio-temporal data modeling with applications to weather and disease
… In such cases, it is beneficial to use spatio-temporal modeling to account for trends and the correlation of nearby observations. This thesis explores applications to spatio-temporal modeling. First, a method is developed to model the marginal distribution of spatial extreme values at a large …
-
Barometer-Based Tactile Sensing: Characterization, Processing, and Applications for Dynamic Manipulation
… collection pipeline is developed to generate temporally-continuous, uniformly sampled datasets across the sensor surface. RNN models trained on this data show that temporal modeling improves force prediction accuracy across both designs. To improve angle prediction accuracy, a binning strategy …
-
Gaze-Aware Driver Maneuver Prediction Using Object Detection and Sequential Deep Learning Models for Advanced Driver Assistance Systems
… (GRU), Long Short-Term Memory (LSTM), and the Temporal Convolutional Network (TCN). Results indicate that incorporating gaze-based object detection features slightly increased the time available to anticipate maneuvers but did not improve prediction accuracy. The Temporal Convolutional Network …
-
Efficient Algorithms, Hardware Architectures and Circuits for Deep Learning Accelerators
… for efficient real-time video understanding with temporal redundancy reduction and temporal modeling. Our proposed techniques enrich accelerator designers’ toolkits, pushing the boundaries of energy efficiency for sustainable advances in deep learning.
-
Graph based management of temporal data
… devices and sensors that led to high-volume temporal data generation. Temporal modeling and querying of this huge data have been essential for effective querying and retrieval. However, custom temporal models have the problem of generalizability, whereas the extended temporal models require …
-
Encoder-Agnostic Learned Temporal Matching for Video Classification
… durations, chronological order of events, and temporal variance in feature significance. While methods for temporal modeling do exist, they often require significant architectural changes and expensive retraining, making them impractical for offthe-shelf, fine-tuned large encoders. To overcome …
-
Temporal Reasoning in Clinical Narratives: From Information Extraction to Early Disease Detection
… This thesis presents a unified framework for temporally grounded patient modeling that integrates structured event representations, fine-grained temporal reasoning, and scalable predictive architectures. Initial experiments show that concept-based models paired with visit-level temporal …
-
PROBABILISTIC AND DEEP LEARNING APPROACHES TO MODELING BIOLOGICAL SYSTEMS
… probabilistic and deep learning methods for modeling biological systems across various scales, with a specific focus on cancer. The aim is to develop models that are both quantitatively rigorous and biologically meaningful. In the first part, I present a hierarchical Bayesian extension of …
-
Machine Learning for Predicting Prosthetic Limb Movements
… thereby limiting their ability to capture the temporal changes of muscle activity. As a result, these approaches often lead to poor accuracy, robustness, and generalization. Limited experimental validation has been conducted on sequence-based machine learning approaches using temporal sEMG data …
-
Leveraging Temporal Dynamics to Enhance Radar-Based Object Detection in Adverse Weather for Autonomous Vehicles
… focused on spatial resolution enhancement, the temporal dimension remains significantly underexplored. Temporal modeling can provide critical benefits such as trajectory continuity, dynamic object discrimination, and resilience against transient noise and false reflections. Yet, most methods …
-
Learning Based Objective QoE Models Across Interactive and Immersive Media
… The proposed methodology demonstrates how QoE modeling principles can be adapted to different media types, learning paradigms, and deployment settings. Each study corresponds to a peer-reviewed publication, collectively forming a systematic progression of research that advances toward a …
-
Predicting Flood Risks to City Infrastructure Systems Utilizing Scalable, Time Sensitive Modeling
… the common practice simply changed the flood modeling to pluvial oriented, keeping the rest of the risk tool components identical for the different flood mechanisms. For pluvial flooding, existing urban flood modeling tools such as SWMM and PC-SWMM are limited by their catchment-based …
-
Temporal Graph Record Linkage and k-Safe Approximate Match
… expanded to perform social network analysis and temporal data modeling. For human services, temporal modeling can reveal how policy changes and treatments affect clients over time and social network analysis can determine the effects of these on whole families by facilitating family linkage.
Page 1 of 2