23 citations · 42 across the 15 of their papers we have counts for
16 papers
FuzzyLogic.jl: a Flexible Library for Efficient and Productive Fuzzy Inference
Luca Ferranti, Jani Boutellier
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…
TBPos: Dataset for Large-Scale Precision Visual Localization
Masud Fahim, Ilona Söchting, Luca Ferranti +2
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 s…
SADT: Combining Sharpness-Aware Minimization with Self-Distillation for Improved Model Generalization
Masud An-Nur Islam Fahim, Jani Boutellier
Methods for improving deep neural network training times and model generalizability consist of various data augmentation, regularization, and optimization approaches, which tend to…
Fault-Tolerant Collaborative Inference through the Edge-PRUNE Framework
Jani Boutellier, Bo Tan, Jari Nurmi
Collaborative inference has received significant research interest in machine learning as a vehicle for distributing computation load, reducing latency, as well as addressing priva…
Multiple Offsets Multilateration: a new paradigm for sensor network calibration with unsynchronized reference nodes
Luca Ferranti, Kalle Åström, Magnus Oskarsson +2
Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems requ…
Edge-PRUNE: Flexible Distributed Deep Learning Inference
Jani Boutellier, Bo Tan, Jari Nurmi
Collaborative deep learning inference between low-resource endpoint devices and edge servers has received significant research interest in the last few years. Such computation part…
Convolutional Neural Network-based Efficient Dense Point Cloud Generation using Unsigned Distance Fields
Abol Basher, Jani Boutellier
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…
Homotopy Continuation for Sensor Networks Self-Calibration
Luca Ferranti, Kalle Åström, Magnus Oskarsson +2
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 a…
LightSAL: Lightweight Sign Agnostic Learning for Implicit Surface Representation
Abol Basher, Muhammad Sarmad, Jani Boutellier
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 concentrate…
Can You Trust Your Pose? Confidence Estimation in Visual Localization
Luca Ferranti, Xiaotian Li, Jani Boutellier +1
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 fo…
Sensor Networks TDOA Self-Calibration: 2D Complexity Analysis and Solutions
Luca Ferranti, Kalle Åström, Magnus Oskarsson +2
Given 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…
Binarized Convolutional Neural Networks for Efficient Inference on GPUs
Mir Khan, Heikki Huttunen, Jani Boutellier
Convolutional neural networks have recently achieved significant breakthroughs in various image classification tasks. However, they are computationally expensive,which can make the…
Embedded Implementation of a Deep Learning Smile Detector
Pedram Ghazi, Antti P. Happonen, Jani Boutellier +1
In this paper we study the real time deployment of deep learning algorithms in low resource computational environments. As the use case, we compare the accuracy and speed of neural…
PRUNE: Dynamic and Decidable Dataflow for Signal Processing on Heterogeneous Platforms
Jani Boutellier, Jiahao Wu, Heikki Huttunen +1
The majority of contemporary mobile devices and personal computers are based on heterogeneous computing platforms that consist of a number of CPU cores and one or more Graphics Pro…
Parallel Digital Predistortion Design on Mobile GPU and Embedded Multicore CPU for Mobile Transmitters
Kaipeng Li, Amanullah Ghazi, Chance Tarver +6
Digital predistortion (DPD) is a widely adopted baseband processing technique in current radio transmitters. While DPD can effectively suppress unwanted spurious spectrum emissions…
Executing Dynamic Data Rate Actor Networks on OpenCL Platforms
Jani Boutellier, Ilkka Hautala
Heterogeneous computing platforms consisting of general purpose processors (GPPs) and graphics processing units (GPUs) have become commonplace in personal mobile devices and embedd…