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 174 for “"self-supervised"”.
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Federated self-supervised learning
… current FL practices predominantly focus on supervised learning tasks, necessitating the availability of high-quality, domain-specific labels alongside the data. This prerequisite constrains the implementation of FL in numerous real-world applications where access to such labels at the edge …
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Self-Supervised Learning for Geometry
… deep learning problems. Differ from conventional supervised learning methods that using expensive annotations as the supervisory signal, we advocate for the use of geometry as a supervisory signal to improve the perceptual capabilities in robots, namely Geometry Self-supervision. With the geometry …
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Structural Self-Supervised Objectives for Transformers
In this Thesis, we leverage unsupervised raw data to develop more efficient pre-training objectives and self-supervised tasks that align well with downstream applications. In the first part, we present three alternative objectives to BERT’s Masked Language Modeling (MLM), namely Random Token …
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Self-supervised multi-contrast MRI denoising
… accuracy. This thesis presents the "Corruption2Self" (C2S) framework, a self-supervised method for multi-contrast MRI denoising. C2S utilizes self-generated pseudo-labels from noisy data to enhance contrast fusion and Signal-to-Noise Ratio (SNR), providing a robust solution that facilitates …
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Self-Supervised Learning for Speech Processing
Deep neural networks trained with supervised learning algorithms on large amounts of labeled speech data have achieved remarkable performance on various spoken language processing applications, often being the state of the arts on the corresponding leaderboards. However, the fact that training …
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Visual Domain Generalization via Self-Supervised Learning
L'abstract è presente nell'allegato / the abstract is in the attachment
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Self-supervised learning frameworks for IoT applications
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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Structuring Representation Geometry in Self-Supervised Learning
… We investigate this question in the context of self-supervised learning, a paradigm that extracts meaningful representations by leveraging the structure of the data itself without relying on explicit labels. Specifically, we propose adding additional geometric structure to the embedding space by …
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CellMincer: Self-Supervised Denoising of Functional Imaging
… a model. This thesis introduces CellMincer, a self-supervised deep neural network for denoising functional imaging. By exploiting a combination of spatiotemporally local contexts and precomputed global features, CellMincer outperforms comparable algorithms at denoising several modes of optical …
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Self-supervised Learning Methods for Vision-based Tasks
… many machine learning models. Among them, self-supervised learning appears as an efficient solution capable of training powerful and generalizable models. More specifically, instead of relying on human-generated labels, it proposes training objectives that use ``labels'' generated from the …
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Self-supervised Learning of Monocular Depth from Video
… problem of monocular depth estimation via self-supervised learning from RGB-only videos. Although existing work has shown partial excellent results in benchmark datasets, there remain several vital challenges that limit the use of these algorithms in general scenarios. To summarize, my …
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Self-Supervised Audio-Visual Speech Diarization and Recognition
Many real world use cases of automatic speech recognition (ASR) contain video and multiple speakers, such as TV broadcasts and video conferences. However, state-of-the-art end-to-end multimodal ASR models generally do not support diarization. This thesis extends one such model, AV-HuBERT, to …
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SLAM-aware, self-supervised perception in mobile robots
… ability to perform GP Saided SLAM, we develop a self-supervised visual-Slam front-end capable of performing visual ego-motion, and vision-based loop-closure recognition in mobile robots. We propose a novel, generative model solution that it is able to predict ego-motion estimates from optical …
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Self-Supervised ECG Learning for Multimodal Clinical Tasks
… combinations. We first introduce ECG-JEPA, a self-supervised encoder pretrained on multiple ECG datasets to learn generalizable time series representations. This unimodal pretraining improves ECG classification, achieving a 23-point AUC gain on the underrepresented Ga dataset. We then align …
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Self-supervised Learning for IMU-based Human Activity Recognition
… units. In this thesis, we propose the use of self-supervised learning for human activity recognition using the tri-axial data collected from the smartphone-embedded accelerometers. To address the limitations of fully-supervised learning, mainly reliance on labeled data, we propose two …
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Contrasting with adversarial examples improves self-supervised representation learning
DSpace SAF Submission Ingestion Package generated from Vireo submission #18414 on 2022-11-16 at 10:56:42
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Self-supervised learning of spatiotemporal features from video colorization
The student, Zubin Pahuja, accepted the attached license on 2019-07-19 at 13:10.
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Self-supervised learning for data-efficient human activity recognition
… data-efficient. First, we proposed a new semi-supervised training pipeline that combines self-supervised learning and knowledge distillation to effectively leverage large-scale unlabelled datasets for human activity recognition. This helps models generalise better across different users by …
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