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In this paper we target the color transfer estimation problem, when we have pixel-to-pixel correspondences. We present a feature-based method, that robustly fits color transforms to data containing gross outliers. Our solution is based on an optimal inlier maximization algorithm that maximizes the number of inliers in polynomial time. We introduce a simple feature detector and descriptor based on
In this paper we present a unified formulation for a large class of relative pose problems with radial distortion and varying calibration. For minimal cases, we show that one can eliminate the number of parameters down to one to three. The relative pose can then be expressed using varying calibration constraints on the fundamental matrix, with entries that are polynomial in the parameters. We can
This thesis proposes approaches and models to increase the energy saving of the User Equipment (UE) in Long-Term Evolution (LTE) and 5G. The focus is mainly on Discontinuous Reception (DRX), the UE energy saving mechanism that was first introduced in LTE and will play an important role in 5G too.In this thesis, we take two main approaches. The first approach is based on joint optimization of DRX a
Atmospheric inversions are used to derive constraints on the net sources and sinks of CO2 and other stable atmospheric tracers from their observed concentrations. The resolution and accuracy that the fluxes can be estimated with depends, among other factors, on the quality and density of the observational coverage, on the precision and accuracy of the transport model used by the inversion to relat
Regression via classification (RvC) is a common method used for regression problems in deep learning, where the target variable belongs to a set of continuous values. By discretizing the target into a set of non-overlapping classes, it has been shown that training a classifier can improve neural network accuracy compared to using a standard regression approach. However, it is not clear how the set
While biometric authentication for commercial use so far mainly has been used for local device unlock use cases, there are great opportunities for using it also for central authentication such as for remote login. However, many current biometric sensors like for instance mobile fingerprint sensors have too large false acceptance rate (FAR) not allowing them, for security reasons, to be used in lar
In recent years, great progress has been made on the problem of 3D scene reconstruction using depth sensors. On a large scale, these reconstructions look impressive, but often many fine details are lacking due to limitations in the sensor resolution. In this paper we combine two well-known principles for recovery of 3D models, namely fusion of depth images with photometric stereo to enhance the de
In this paper we are proposing a new member in the SNOW family of stream ciphers, called SNOW-V. The motivation is to meet an industry demand of very high speed encryption in a virtualized environment, something that can be expected to be relevant in a future 5G mobile communication system. We are revising the SNOW 3G architecture to be competitive in such a pure software environment, making use o
We improve iterative decoding of the moderate density parity-check codes, recently suggested as code candidates in the McEliece public key cryptosystem. In case of bit-flipping (BF) decoder failure, the code parity-check matrix is extended by adding auxiliary variable nodes based on reliability information from the BF decoder. Then iterative decoding is applied to the extended parity-check matrix.
Precipitation in clouds can form by either warm-rain or ice crystal processes, referred to as warm and cold formation pathways, respectively. Here, we investigate the warm and cold pathway contributions to surface precipitation in simulated continental convective storms. We analyze three contrasting convective storms that are cold-based, slightly warm-based and very warm-based. We apply tracer-tag
In post-quantum cryptography (PQC), Learning With Errors (LWE) is one of the dominant underlying mathematical problems. For example, in NIST’s PQC standardization process, the Key Encapsulation Mechanism (KEM) protocol chosen for standardization was Kyber, an LWE-based scheme. Recently the dual attack surpassed the primal attack in terms of concrete complexity for solving the underlying LWE proble
In LWE-based KEMs, observed decryption errors leak information about the secret key in the form of equations or inequalities. Several practical fault attacks have already exploited such leakage by either directly applying a fault or enabling a chosen-ciphertext attack using a fault. When the leaked information is in the form of inequalities, the recovery of the secret key is not trivial. Recent me
We consider the statistical sparse jump model, a recently developed, robust and interpretable regime switching model, to identify features that drive the return dynamics of the largest cryptocurrencies. The approach simultaneously performs feature selection, parameter estimation, and state classification. Our large number of candidate features comprises cryptocurrency, sentiment, and financial mar
The paper considers multi-hop wireless mesh networks that serve multicast periodic packet traffic. The packets from each packet stream are generated at the stream's source node and traverse a number of wireless nodes in order to reach their multiple destination nodes. Packet periodicity means that a common repeatable frame of time slots is defined and that the packets to be transmitted arrive at t
Semanticrolelabelinghasbecomeakeymodule for many language processing applications such as question answering, information extraction, sentiment analysis, and machine translation. To build an unrestricted semantic role labeler, the first step is to develop a comprehensive proposition bank. However, creating such a bank is a costly enterprise, which has only been achieved for a handful of languages.
In this paper, we describe a system that jointly extracts entities appearing in images and mentioned in their ac- companying captions. As input, the entity linking pro- gram takes a segmented image together with its cap- tion. It consists of a sequence of processing steps: part- of-speech tagging, dependency parsing, and coreference resolution that enables us to identify the entities as well as po
Localization is an important enabling technology for many applications, such as wireless sensor networks, emergency rescue services, civil defense and transportation. Suppose that a room is equipped with several microphones (or sensors), and one person is making a sound while moving around in the room. Can one find microphone and sound source positions as well as reconstruct a room geometry? The a
The central problem of this thesis is locating several sources and simultaneously locating the positions of the sensors. The measurements captured by the sensors are time of arrival (TOA), time difference of arrival (TDOA), unsynchronized TDOA, or received signal strength indication (RSSI), all a variation of distance measurement between sensors and sources. Signals can be either sound or radio fo
