Sökning: "deep models"

Visar resultat 26 - 30 av 400 avhandlingar innehållade orden deep models.

1. 26. Design Methods and Processes for ML/DL models

   Författare :Meenu Mary John; Helena Holmström Olsson; Jan Bosch; Maria Paasivaara; Malmö universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Machine Learning; Deep Learning; Development; Deployment; Evolution;

   Sammanfattning : Context: With the advent of Machine Learning (ML) and especially Deep Learning (DL) technology, companies are increasingly using Artificial Intelligence (AI) in systems, along with electronics and software. Nevertheless, the end-to-end process of developing, deploying and evolving ML and DL models in companies brings some challenges related to the design and scaling of these models. LÄS MER

3. 27. Deriving biomarkers from computed tomography using deep learning

   Författare :Meera Srikrishna; Göteborgs universitet; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; CT; MRI; convoluted neural networks; deep learning; Dementia; Alzheimer s disease; Normal pressure hydrocephalus; brain segmentation;

   Sammanfattning : X-ray computed tomography (CT) and magnetic resonance imaging (MRI) are widely used structural neuroimaging modalities. For brain atrophy assessment and volumetric quantification using automated methods, MRI is the preferred modality due to its superior soft tissue contrast. LÄS MER

4. 28. Deep Learning For Model-Based Multi-Object Tracking

   Författare :Juliano Pinto; Chalmers tekniska högskola; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; multi-object smoothing; multi-object tracking; Deep learning; multi-object tracking performance measures;

   Sammanfattning : Multi-object tracking (MOT) is the task of estimating the state of multiple objects based on noisy sensor measurements. MOT is essential in various applications, such as pedestrian monitoring, vehicle tracking, animal behavior analysis, and others. LÄS MER

5. 29. Adapting Deep Learning for Microscopy: Interaction, Application, and Validation

   Författare :Ankit Gupta; Carolina Wählby; Ida-Maria Sintorn; Ola Spjuth; Andreas Hellander; Philip Kollmannsberger; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Microscopy; Human-in-the-Loop; Semi-Supervised Learning; Application-Specific Analysis; Image Classification; Image-to-Image Translation; Template Matching; Computerized Image Processing; Datoriserad bildbehandling;

   Sammanfattning : Microscopy is an integral technique in biology to study the fundamental components of life visually. Digital microscopy and automation have enabled biologists to conduct faster and larger-scale experiments with a sharp increase in the data generated. LÄS MER

7. 30. Source Code Representations of Deep Learning for Program Repair

   Författare :Zimin Chen; Martin Monperrus; Benoit Baudry; Zhendong Su; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Code Representation; Deep Learning; Program Repair; Datalogi; Computer Science;

   Sammanfattning : Deep learning, leveraging artificial neural networks, has demonstrated significant capabilities in understanding intricate patterns within data. In recent years, its prowess has been extended to the vast domain of source code, where it aids in diverse software engineering tasks such as program repair, code summarization, and vulnerability detection. LÄS MER