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 20 of 71 for “"Multitask"”.
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Interactive Exploration of Multitask Dependency Networks
Scientists increasingly depend on machine learning algorithms to discover patterns in complex data. Two examples addressed in this dissertation are identifying how information sharing among regions of the brain develops due to learning; and, learning dependency networks of blood proteins associated …
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Multilingual multitask joint neural information extraction
… knowledge across different models through multitask learning to reduce the need for data annotation. To maximize the knowledge being transferred, we design a unified and extendable architecture that integrates multiple transfer approaches. After that, we extend this framework to more IE …
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A New Framework for Semisupervised, Multitask Learning
To conclude, we interpret the internal representation of the model and use it to perform unsupervised scene discovery. Defining a meaningful vocabulary for scene discovery is a challenging problem that has important consequences for object recognition. We consider scenes to depict correlated …
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Regularization based multitask learning with applications in computational biology
… Zum anderen betrachten wir Methoden des Multitask Learnings, bei dem Informationen wechselseitig zwischen verschiedenen Domänen geteilt werden. Für den Fall von Domain Adaptation entwickeln wir Erweiterungen von etablierten Algorithmen zur regularisierten Risiko Minimierung, die es …
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DETECTION OF OPERATOR PERFORMANCE BREAKDOWN IN A MULTITASK ENVIRONMENT
The purpose of this dissertation work is: 1) to empirically demonstrate an extreme human operator’s state, performance breakdown (PB), and 2) to develop an objective method for detecting such a state. PB has been anecdotally described as a state where the human operator “loses control of the …
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Utilizing Multitask Transfer Learning for Sonographic Rheumatoid Arthritis Synovitis Grading
… Therefore, the current research proposes a Multitask Transfer Learning (MTL) framework for sonographic RA synovitis grading of Ultrasound (US) images in Brightness mode (B-Mode) and Power Doppler mode.</p> <p>In the medical community, the lack of reliability of scoring these images has been …
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Deep Learning-Enabled Multitask System for Exercise Recognition and Counting
… other two tasks. In this thesis, we propose a multitask system covering the three domains. Different from the methodology used in the literature, heatmaps which are the byproducts of 2D human pose estimation models are adopted for exercise recognition and counting. Recent heatmap processing …
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Probabilistic Human Arm Motion Prediction via Structured Multitask Variational Gaussian Processes
… address this gap, we propose a novel structured multitask variational GP framework that explicitly incorporates joint dependencies to reflect human kinematics. We further enhance this framework by integrating angular velocity constraints, which improve the physical plausibility of predictions. …
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Efficient Prediction of Quantum Chemical Properties with Multitask Gaussian Process Regression
Multitask inference offers an efficient approach to bringing together multiple sources of information to train a surrogate model to predict chemical properties. In this thesis, we explore the task of inferring probability distributions on quantities of interest when we have access to a limited …
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A Multitask Deep Learning Framework for Clinical Decision-Making in Assisted Reproductive Technology
… weighting for dynamic task balancing. This multitask approach achieves near-state-of-the-art performance (protocol AUC = 0.79, pregnancy AUC = 0.74) while offering practical deployment advantages such as faster inference and fewer parameters than equivalent single-task ensembles. This …
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Adapting Whisper for Modern Greek and Dialectal Speech Recognition: A Multitask and Curriculum Learning Approach
Οι πρόσφατες εξελίξεις στα μεγάλης κλίμακας αυτοεπιβλεπόμενα μοντέλα ομιλίας έχουν οδηγήσει σε σημαντικές βελτιώσεις στην αυτόματη αναγνώριση ομιλίας (ASR), ιδίως σε γλώσσες με πλούσιους γλωσσικούς πόρους. Παρ’ όλα αυτά, η προσαρμογή των μοντέλων αυτών σε γλώσσες χαμηλών και μεσαίων πόρων, καθώς …
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Problems With Auditory Alarms in Anesthesia and Tests of a Proposed Solution: Multimodal Multitask Performance With an Auditory Display
Auditory alarms are used pervasively for patient-monitoring equipment to warn of potential problems, despite widely reported shortcomings in their design. Problems include high rates of false alarms; interruptive, uninformative, stress-inducing acoustic profiles for alarm sounds; and alarms that …
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Machine Learning towards General Medical Image Segmentation
… algorithms. We approached segmentation as a multitask shape regression problem, simultaneously predicting coordinates on an object's contour while jointly capturing global shape information. Shape regression models inherent point correlations to recover ambiguous boundaries not supported by …
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AGING-RELATED DECREMENTS DURING THE ACTIVITIES OF THE TIMED UP AND GO TEST WHEN COMBINED WITH MOTOR TASK AND VISUAL STIMULATION
… and jerk of sit-to-stand and stand-to-sit; and multitask cost. Multitask cost reflects the change in the motor behavior that occurs due to high attentional demanding conditions, with the lowest multitask cost reflecting poorer motor performance. The multitask cost was calculated as the percent …
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Object Detection on Unmanned Arial Vehicles Dataset Using Adaptive HydraNet
… this limitation by introducing AHydraNet, a multitask learning module based on the low-cost dynamic multitask architecture HydraNet. AHydraNet is a multilabel classification template with an adaptive threshold that enhances the precision of the detection for small and medium-sized objects. We …
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Training Physics-Guided Neural Networks with Multiple Constraints: An Application in Lake Ecology Modeling
… with multiple constraints, we explore the use of multitask learning methods to counteract gradient pathologies that arise when training PGNNs. Our results suggest that multitask learning approaches can improve in-distribution performance in certain architectures, but they do not enhance zero- shot …
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Yield Curves and Macro Variables Interactions and Predictions
… predicted yield curves based on ANN Regression Multitask learning, and lastly, we predicted our five macro variables based on three different ANN Classifiers, in order to generalize and present results that are not specific to a country, or region, or model. The most persistence trend, amongst …
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Learning Representations for Limited and Heterogeneous Medical Data
… learning, contrastive learning, meta-learning, multitask learning, and robust learning. We present studies with different medical applications, such as clinical language translation, ultrasound image classification and segmentation, medical image retrieval, skin diagnosis classification, …
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Self-Supervised ECG Learning for Multimodal Clinical Tasks
… performance, highlighting the value of multitask time series pretraining and modular fusion for clinical AI.
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