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 43 for “"Multimodal learning"”.
-
Polar Region Sea Ice Classification With Multimodal Learning
… of sea ice. This thesis presents a multimodal learning approach for classifying polar sea ice thickness using both satellite imagery and altimetry data. The objective is to distinguish between thick ice, thin ice, and open water, which are crucial for understanding ice dynamics and …
-
Generative and Multimodal Learning for Vision and Language
L'abstract è presente nell'allegato / the abstract is in the attachment
-
Multimodal Learning for Disease Diagnosis and Progression Modeling
… complex, multifaceted nature of AD. Therefore, multimodal learning addresses this limitation by integrating complementary information across sources, but conventional fusion strategies, such as early feature concatenation and late decision-level fusion, often model modalities independently and …
-
Multimodal learning and language models for enhanced knowledge representations
Machine learning with modern neural architectures, particularly large-scale language models, has enabled impressive progress across diverse problem domains such as natural language processing, graph representation learning, and tabular data analysis. However, these successes have predominantly …
-
Bridging Multimodal Learning and Planning for Intelligent Task Assistance
Task-assistance systems provide adaptive, multimodal guidance for complex, step-based activities such as cooking and DIY projects. A central challenge lies in enabling these systems to interpret real-world scenarios—understanding user intent from verbal, visual, or textual cues and generating …
-
Multimodal Learning Methods for the Fundamentals of Atomic Force Microscopy
… of an Atomic Force Microscope (AFM), through multimodal learning methods to assess whether students have an easier time understanding unintuitive concepts. This study used a custom lowcost haptic feedback controller as the main interaction tool for students to “feel” the forces that an AFM tip …
-
Conditional Neural Language Models for Multimodal Learning and Natural Language Understanding
… recurrent neural networks with applications to multimodal learning and natural language understanding. We first introduce a LSTM encoder for learning visual-semantic embeddings for ranking the relevance of text to images in a joint embedding space. Next we introduce three log-bilinear models for …
-
Instruction Mining from Images: Constructing a Synthetic Dataset for Multimodal Learning
… και των πολυτροπικών μοντέλων όρασης–γλώσσας (Multimodal Large Language Models – MLLMs) έχει οδηγήσει στην ανάπτυξη συστημάτων ικανών να συνδυάζουν οπτική και γλωσσική πληροφορία για την εκτέλεση σύνθετων εργασιών συλλογισμού, κατανόησης εγγράφων, OCR, οπτικού διαλόγου και multimodal …
-
Ranking features used in modeling student collaboration using multimodal learning analytics
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01
-
Dynamic multimodal learning: Empowering ai to interpret the temporally dynamic world through vision, language, audio, and video
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01
-
Neural techniques for modeling visually grounded speech
… loss. In Chapter 1, I provide a background on multimodal learning and motivate the need for further research in the area. In addition, I give an overview of Harwath et al. (2016)'s model, variants of which will be used throughout the rest of the thesis. In Chapter 2, I present a quantitative …
-
Using unfolding case studies in a traditional classroom setting to enhance critical thinking skills in pre-licensure Bachelor of Science Nursing students
… students to determine if the use of multimodal learning (visual, auditory, reading, and kinesthetic) opportunities throughout UCS improved CTS in the classroom setting, clinical setting, and preparing for course content exams and, (d) explore if the above-mentioned subset of BSN …
-
Detecting Multimodal Behaviors for Neurodegenerative Disease
… data and show its use in detecting specific multimodal learning behaviors. Furthermore, this thesis will explore recommendations for working with eye-tracking systems and outline future steps towards developing a multimodal classification model to automate early diagnosis of neurodegenerative …
-
The impact of multiliteracies and multimodality on ESL learners: Using Neuroimaging Technologies
… is an important literacy pedagogy addressing multimodal learning and cultural and linguistic diversity. This study used functional near infrared spectroscopy (fNIRS) to investigate the association of multiliteracies learning on adult English Second Language (ESL) students’ performance through …
-
Large-scale acoustic scene analysis with deep residual networks
… surpassing the state-of-the-art without transfer learning from a large dataset. We also analyze the output activations of the network and find that the models are able to localize audio events when a finer time resolution is needed. In addition, we use this model in exploring multimodal learning, …
-
Multimodal Representation Learning for Medical Image Analysis
My thesis develops machine learning methods that exploit multimodal clinical data to improve medical image analysis. Medical images capture rich information of a patient’s physiological and disease status, central in clinical practice and research. Computational models, such as artificial neural …
-
Computational Models for Binaural Sound Source Localization and Sound Understanding
… are achieved under real-world environments. A multimodal learning scheme is proposed with the aid of vision to realize autonomous learning for the 3D binaural localization. No human instructors need to be involved. A generic model is presented for sound source understanding. No labelled …
-
Deep Learning Based Approaches For Low Cost Defense Detection
… structures. This thesis investigates the use of multimodal deep learning techniques to assist in pul- monary fibrosis detection by integrating chest X-ray images with corresponding radiology reports. Pretrained medical vision–language models, including BioViL-T, PubMedCLIP, and KAD, are used to …
Page 1 of 3