OSUVA - Selaus tekijän "https://orcid.org/0000-0001-7606-3655" mukaan
Aineistot 1-12 / 12
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Can You Trust Your Pose? Confidence Estimation in Visual Localization
(IEEE, 05.05.2021)
articleCamera 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 ... -
DC-DFFN: Densely Connected Deep Feature Fusion Network With Sign Agnostic Learning for Implicit Shape Representation
(IEEE, 11.05.2023)
articleReconstructing 3D surfaces from raw point cloud data is still a challenging and complex problem in computer vision and graphics. Recently emerged neural implicit representations model 3D surfaces implicitly in arbitrary ... -
Decidable Variable-Rate Dataflow for Heterogeneous Signal Processing Systems
(IEEE, 14.05.2020)
articleDynamic dataflow models of computation have become widely used through their adoption to popular programming frameworks such as TensorFlow and GNU Radio. Although dynamic dataflow models offer more programming freedom, they ... -
Homotopy Continuation for Sensor Networks Self-Calibration
(IEEEEuropean Association for Signal Processing (EURASIP), 08.12.2021)
articleGiven 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 ... -
I Trust You Dr. Researcher, but not the Company that Handles My Data –Trust in the Data Economy
(University of Hawaii, 03.01.2024)
articleIn the rising era of artificial intelligence (AI), learning machinery and hyper surveillance, trust is a sought-after attribute. The General Data Protection Regulation (GDPR) was introduced to increase individuals’ control ... -
Multiple Offsets Multilateration : A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes
(IEEE, 27.04.2022)
articlePositioning 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 ... -
Sensor Networks TDOA Self-Calibration : 2D Complexity Analysis and Solutions
(IEEE, 13.05.2021)
articleGiven a network of receivers and transmitters, the process of determining their positions from measured pseudoranges is known as network self-calibration. In this paper we consider 2D networks with synchronized receivers ... -
SPHERE-DNA : Privacy-Preserving Federated Learning for eHealth
(IEEE, 02.06.2023)
articleThe rapid growth of chronic diseases and medical conditions (e.g. obesity, depression, diabetes, respiratory and musculoskeletal diseases) in many OECD countries has become one of the most significant wellbeing problems, ... -
SS-TTA : Test-Time Adaption for Self-Supervised Denoising Methods
(IEEE, 14.08.2023)
articleEven though image denoising has already been studied for decades, recent progress in deep learning has provided novel and considerably better results for this classical signal reconstruction problem. One of the most ... -
TBPos: Dataset for Large-Scale Precision Visual Localization
(Springer, 27.04.2023)
articleImage 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 ... -
TTADF : Power Efficient Dataflow-Based Multicore Co-Design Flow
(Institute of Electrical and Electronics Engineers (IEEE), 27.04.2019)
articleThe era of mobile communications and the Internet of Things (IoT) has introduced numerous challenges for mobile processing platforms that are responsible for increasingly complex signal processing tasks from different ... -
VR-PRUNE : Decidable Variable-Rate Dataflow for Signal Processing Systems
(IEEE, 25.03.2022)
articleThe dataflow concept has been successfully used for modeling and synthesizing signal processing applications since decades, and recently, dataflow has also been discovered to match the computation model of machine learning ...
