Results 11 to 20 of about 356,686 (298)
Unsupervised two-class and multi-class support vector machines for abnormal traffic characterization [PDF]
, 2009 Although measurement-based real-time traffic classification has received considerable research attention, the timing constraints imposed by the high accuracy requirements and the learning phase of the algorithms employed still remain a challenge. In this
Hutchison, D. +3 more
core +5 more sources
Unsupervised Part Discovery by Unsupervised Disentanglement [PDF]
, 2021 GCPR 2020 (Oral)
Sandro Braun +2 more
openaire +4 more sources
Unsupervised two-class & multi-class support vector machines for abnormal traffic characterization. [PDF]
, 2009 Although measurement-based real-time traffic classification has received considerable research attention, the timing constraints imposed by the high accuracy requirements and the learning phase of the algorithms employed still remain a challenge. In this
Kim, Hyun-chul +7 more
core +4 more sources
CoRR, 2021 This paper studies "unsupervised finetuning", the symmetrical problem of the well-known "supervised finetuning". Given a pretrained model and small-scale unlabeled target data, unsupervised finetuning is to adapt the representation pretrained from the source domain to the target domain so that better transfer performance can be obtained.
Suichan Li +7 more
openaire +2 more sources
American Journal of Orthodontics and Dentofacial Orthopedics, 2023 This work was supported by the Flemish Government under the “Onderzoeksprogramma Artifici€ele Intelligentie (AI) Vlaanderen ...
Dirk Valkenborg +3 more
openaire +3 more sources
Unsupervised Volumetric Animation
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 We propose a novel approach for unsupervised 3D animation of non-rigid deformable objects. Our method learns the 3D structure and dynamics of objects solely from single-view RGB videos, and can decompose them into semantically meaningful parts that can be tracked and animated.
CHAI MENGLEI +7 more
openaire +5 more sources
Evaluating Unsupervised Denoising Requires Unsupervised Metrics
CoRR, 2022 Unsupervised denoising is a crucial challenge in real-world imaging applications. Unsupervised deep-learning methods have demonstrated impressive performance on benchmarks based on synthetic noise. However, no metrics are available to evaluate these methods in an unsupervised fashion. This is highly problematic for the many practical applications where
Adria Marcos-Morales +7 more
openaire +4 more sources
Over-the-Counter Use of Medical Abortion Pills: A Prospective Cohort Study [PDF]
Journal of Clinical and Diagnostic Research, 2023 Introduction: Medical abortion is a safe intervention in the first trimester that requires access to accurate information and the support of a trained healthcare provider.
Reema Kumari +2 more
doaj +1 more source
Unsupervised discovery of morphemes [PDF]
Proceedings of the ACL-02 workshop on Morphological and phonological learning -, 2002 We present two methods for unsupervised segmentation of words into morpheme-like units. The model utilized is especially suited for languages with a rich morphology, such as Finnish. The first method is based on the Minimum Description Length (MDL) principle and works online. In the second method, Maximum Likelihood (ML) optimization is used.
Mathias Creutz, Krista Lagus
openaire +3 more sources
Video Scene Segmentation of TV Series Using Multimodal Neural Features
Series. International journal of tv serial narratives, 2019 Scene segmentation of a video, a book or TV series allows to organize them into Logical Story Units and is an essential step for representing, extracting and understanding their narrative structures.
Aman Berhe +2 more
doaj +1 more source