Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Boutellier, Jani"'
Autor:
Ferranti, Luca, Boutellier, Jani
Publikováno v:
2023 IEEE International Conference on Fuzzy Systems (FUZZ)
This paper introduces \textsc{FuzzyLogic.jl}, a Julia library to perform fuzzy inference. The library is fully open-source and released under a permissive license. The core design principles of the library are: user-friendliness, flexibility, efficie
Externí odkaz:
http://arxiv.org/abs/2306.10316
Image based localization is a classical computer vision challenge, with several well-known datasets. Generally, datasets consist of a visual 3D database that captures the modeled scenery, as well as query images whose 3D pose is to be discovered. Usu
Externí odkaz:
http://arxiv.org/abs/2302.09825
Methods for improving deep neural network training times and model generalizability consist of various data augmentation, regularization, and optimization approaches, which tend to be sensitive to hyperparameter settings and make reproducibility more
Externí odkaz:
http://arxiv.org/abs/2211.00310
Collaborative inference has received significant research interest in machine learning as a vehicle for distributing computation load, reducing latency, as well as addressing privacy preservation in communications. Recent collaborative inference fram
Externí odkaz:
http://arxiv.org/abs/2206.08152
Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems require the computation of the positions of receivers and/or transmitters
Externí odkaz:
http://arxiv.org/abs/2205.11299
Collaborative deep learning inference between low-resource endpoint devices and edge servers has received significant research interest in the last few years. Such computation partitioning can help reducing endpoint device energy consumption and impr
Externí odkaz:
http://arxiv.org/abs/2204.12947
Autor:
Basher, Abol, Boutellier, Jani
Dense point cloud generation from a sparse or incomplete point cloud is a crucial and challenging problem in 3D computer vision and computer graphics. So far, the existing methods are either computationally too expensive, suffer from limited resoluti
Externí odkaz:
http://arxiv.org/abs/2203.11537
Given a sensor network, TDOA self-calibration aims at simultaneously estimating the positions of receivers and transmitters, and transmitters time offsets. This can be formulated as a system of polynomial equations. Due to the elevated number of unkn
Externí odkaz:
http://arxiv.org/abs/2108.00667
Recently, several works have addressed modeling of 3D shapes using deep neural networks to learn implicit surface representations. Up to now, the majority of works have concentrated on reconstruction quality, paying little or no attention to model si
Externí odkaz:
http://arxiv.org/abs/2103.14273
Camera pose estimation in large-scale environments is still an open question and, despite recent promising results, it may still fail in some situations. The research so far has focused on improving subcomponents of estimation pipelines, to achieve m
Externí odkaz:
http://arxiv.org/abs/2010.00347