Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Mudur, Sudhir P."'
Convolutional Neural Networks (CNNs) excel in local spatial pattern recognition. For many vision tasks, such as object recognition and segmentation, salient information is also present outside CNN's kernel boundaries. However, CNNs struggle in captur
Externí odkaz:
http://arxiv.org/abs/2311.12091
Direct mesh editing and deformation are key components in the geometric modeling and animation pipeline. Mesh editing methods are typically framed as optimization problems combining user-specified vertex constraints with a regularizer that determines
Externí odkaz:
http://arxiv.org/abs/2310.04561
Autor:
Sarfi, Amirmohammad, Karimpour, Zahra, Chaudhary, Muawiz, Khalid, Nasir M., Ravanelli, Mirco, Mudur, Sudhir, Belilovsky, Eugene
Recently, a number of iterative learning methods have been introduced to improve generalization. These typically rely on training for longer periods of time in exchange for improved generalization. LLF (later-layer-forgetting) is a state-of-the-art m
Externí odkaz:
http://arxiv.org/abs/2304.04858
In Continual learning (CL) balancing effective adaptation while combating catastrophic forgetting is a central challenge. Many of the recent best-performing methods utilize various forms of prior task data, e.g. a replay buffer, to tackle the catastr
Externí odkaz:
http://arxiv.org/abs/2303.14771
Continual Learning research typically focuses on tackling the phenomenon of catastrophic forgetting in neural networks. Catastrophic forgetting is associated with an abrupt loss of knowledge previously learned by a model when the task, or more broadl
Externí odkaz:
http://arxiv.org/abs/2203.13381
Recent work studies the supervised online continual learning setting where a learner receives a stream of data whose class distribution changes over time. Distinct from other continual learning settings the learner is presented new samples only once
Externí odkaz:
http://arxiv.org/abs/2203.13307
Personalized recommendations are popular in these days of Internet driven activities, specifically shopping. Recommendation methods can be grouped into three major categories, content based filtering, collaborative filtering and machine learning enha
Externí odkaz:
http://arxiv.org/abs/2101.03054
Autor:
Mokhov, Serguei A., Song, Miao, Singh, Jashanjot, Paquet, Joey, Debbabi, Mourad, Mudur, Sudhir
Visualization requirements in Forensic Lucid have to do with different levels of case knowledge abstraction, representation, aggregation, as well as the operational aspects as the final long-term goal of this proposal. It encompasses anything from th
Externí odkaz:
http://arxiv.org/abs/1808.00118
Action recognition, motion classification, gait analysis and synthesis are fundamental problems in a number of fields such as computer graphics, bio-mechanics and human computer interaction that generate a large body of research. This type of data is
Externí odkaz:
http://arxiv.org/abs/1710.02566
Object classification is one of the many holy grails in computer vision and as such has resulted in a very large number of algorithms being proposed already. Specifically in recent years there has been considerable progress in this area primarily due
Externí odkaz:
http://arxiv.org/abs/1709.07368