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Automated object detection is perhaps the most central task of computer vision and arguably the most difficult one. This paper extends previous work on part-based models by using accurate geometric models both in the learning phase and at detection. In the learning phase manual annotations are used to reduce perspective distortion before learning the part-based models. That training is performed o
What is the computational complexity of geometric model estimation in the presence of noise and outliers? We show that the number of outliers can be minimized in polynomial time with respect to the number of measurements, although exponential in the model dimension. Moreover, for a large class of problems, we prove that the statistically more desirable truncated L2-norm can be optimized with the s
OBJECTIVE: To assess the reliability of knee extensor and flexor muscle strength measurements in persons with late effects of polio. DESIGN: A test-retest reliability study. SUBJECTS: Thirty men and women (mean age 63 (standard deviation 6.4) years) with verified late effects of polio. METHODS: Knee extensor and flexor muscle strength in both lower limbs were measured twice 7 days apart using a Bi
PURPOSE: Physical activity during growth is associated with high peak bone mass and may, as a result, prevent osteoporosis later in life. It is therefore possible that athletic activity during youth could lower the risk of fragility fractures in old age. Though, this is currently unclear and, based on evaluations of surrogate skeletal end point variables in former athletes, we hypothesized that th
Millimeter-wave cellular communication requires beamforming procedures that enable alignment of the transmitter and receiver beams as the user equipment (UE) moves. For efficient beam tracking it is advantageous to classify users according to their traffic and mobility patterns. Research to date has demonstrated efficient ways of machine learning based UE classification. Although different machine
In this paper we consider a collection of relative pose problems which arise naturally in applications for visual indoor navigation using unmanned aerial vehicles (UAVs). We focus on cases where additional information from an onboard IMU is available and thus provides a partial extrinsic calibration through the gravitational vector. The solvers are designed for a partially calibrated camera, for a
3D human pose and shape estimation plays a vital role in many computer vision applications. There are many deep learning based methods attempting to solve the problem only relying on single-view RGB images for training the network. However, since some public datasets are captured from multi-view cameras system, we propose a novel method to tackle the problem by putting optimization-based multi-vie
Emerging fine-grained cloud resource billing creates incentives to review the software execution footprint in virtual environments. Operators can use novel virtual execution environments with ever lower overhead: from virtual machines to containers, to unikernels and serverless functions. However, the execution footprint of security mechanisms in virtualized deployments has either remained the sam
Local pseudorandom generators are a class of fundamental cryptographic primitives having very broad applications in theoretical cryptography. Following Couteau et al.’s work at ASIACRYPT 2018, this paper further studies the concrete security of one important class of local pseudorandom generators, i.e., Goldreich’s pseudorandom generators. Our first attack is of the guess-and
This book constitutes the refereed proceedings of the 14th International Workshop on Post-Quantum Cryptography, PQCrypto 2022, held in College Park, MD, USA, in August 14–18, 2023.The 25 full papers presented in this book were carefully reviewed and selected from 51 submissions. They are categorized in the following topical sections: code-based cryptography; group-action-based cryptography; isogen
Misuse resilience is an important security criterion in the evaluation of the NIST Post-quantum cryptography standardization process. In this paper, we propose new key mismatch attacks against Kyber and Saber, NIST's selected scheme for encryption and one of the finalists in the third round of the NIST competition, respectively. Our novel idea is to recover partial information of multiple secret e
Network Data Analytics Function (NWDAF) is a key component in 5G networks, introduced by 3G Partnership Project (3GPP) standards, that leverages machine learning to optimize network performance. The 3GPP standards mandate that mobile network operators should retrain NWDAF models to maintain accuracy. However, the presence of adversarial user equipment (UE) can introduce corrupted data points durin
Ensuring availability is a critical requirement for the Internet of Things (IoT). CIDER, a recovery architecture, and its follow-up scheme, Lazarus, are solutions to address this issue. CIDER introduced a new hardware module, the Authenticated Watchdog Timer (AWDT), to keep IoT devices running in normal mode as long as trusted authenticated tickets are received from a hub. If valid tickets are not
To resolve the various types of biological ice nuclei (IN) with atmospheric models, an extension of the empirical parameterization (EP) is proposed to predict the active IN from multiple groups of primary biological aerosol particles (PBAPs). Our approach is to utilize coincident observations of PBAP sizes, concentrations, biological composition, and ice nucleating ability. The parameterization or
Pseudo-Random Injections (PRIs) have been used in several applications in symmetric-key cryptography, such as in the idealization of Authenticated Encryption with Associated Data (AEAD) schemes, building robust AEAD, and, recently, in converting a committing AEAD scheme into a succinctly committing AEAD scheme. In Crypto 2024, Bellare and Hoang showed that if an AEAD scheme is already committing,
Automated cryptanalysis has seen a lot of attraction and success in the past decade, leading to new distinguishers or key-recovery attacks against various ciphers. We argue that the improved efficiency and usability of these new tools have been undervalued, especially for design processes. In this article, we break for the first time the classical iterative design paradigm for symmetric-key primit
A new microphysical treatment that includes aerosol–cloud interactions and secondary ice production (SIP) mechanisms is implemented in the convection scheme of the Community Atmosphere Model, version 6 (CAM6). The approach is to embed a 1D Lagrangian parcel model in the bulk convective plume of the existing deep convection parameterization. Aerosol activation, growth processes including collision/
In this paper, we present novel key-recovery attacks on Approximate Homomorphic Encryption schemes, such as CKKS, when employing noise-flooding countermeasures based on non-worst-case noise estimation. Our attacks build upon and enhance the seminal work by Li and Micciancio at EUROCRYPT 2021. We demonstrate that relying on average-case noise estimation undermines noise-flooding countermeasures, ev
