Combined use of airborne laser scanning and hyperspectral imaging for forest inventories

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Notions of surprise and novelty have been used in various experimental and theoretical studies across multiple brain areas and species. However, 'surprise' and 'novelty' refer to different quantities in different studies, which raises concerns about whethe ...

To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double Sérsic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified param ...

In this work, we study online submodular maximization and how the requirement of maintaining a stable solution impacts the approximation. In particular, we seek bounds on the best-possible approximation ratio that is attainable when the algorithm is allowe ...

In this letter we consider mean field type control problems with multiple species that have different dynamics. We formulate the discretized problem using a new type of entropy-regularized multimarginal optimal transport problems where the cost is a decomp ...

The first two chapters develop ML-based models that generate conditional SDF estimates efficiently using conditioning information sets, resulting in minimal pricing errors and superior Sharpe ratios compared to traditional conditional asset pricing models. ...

Implantable bioelectronic devices predominantly use wireless links for communication and/or power transfer. When considering transmitting implanted antennas, electromagnetic radiation through biological media is highly attenuated, and previous work has sho ...

Image steganalysis, detecting hidden data in digital images, is essential for enhancing digital security. Traditional steganalysis methods typically rely on large, pre-labeled image datasets, which are difficult and costly to compile. To address this, this ...

Macromolecular mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is a quick tool for biochemical analysis. In combination with algorithms for automated data analysis and interpretation, it has wide appli ...

Synthesizability in generative molecular design remains a pressing challenge. Existing methods to assess synthesizability include heuristics-based metrics or retrosynthesis models which predict a synthetic pathway. By contrast, an explicit approach anchors ...

The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, ...

A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation of algorithms t ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

Banner clouds are clouds in the lee of steep mountains or sharp ridges on otherwise cloud-free days. Previous studies identified key mechanisms and preferred flow conditions on the basis of idealized Large-Eddy Simulations, but it remained unclear to what ...

Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...

Let k be a field, and let L be an etale k-algebra of finite rank. If a is an element of k(x), let X-a be the affine variety defined by N-L/k(x) = a. Assuming that L has at least one factor that is a cyclic field extension of k, we give a combinatorial desc ...

Automatic speech recognition (ASR) systems are well known to perform poorly on dysarthric speech. Previous works have addressed this by speaking rate modification to reduce the mismatch with typical speech. Unfortunately, these approaches rely on transcrib ...

Last-mile delivery in the logistics chain contributes to congestion in urban networks due to frequent stops. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery but relies heavily on the availability of occasional couriers. In ...

Combined use of airborne laser scanning and hyperspectral imaging for forest inventories

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Surprise and novelty in the brain

Euclid preparation: LXVII. Deep learning true galaxy morphologies for weak lensing shear bias calibration

The Cost of Consistency: Submodular Maximization with Constant Recourse

Mean Field Type Control With Species Dependent Dynamics via Structured Tensor Optimization

Machine Learning Applications to Conditional Asset Pricing: Attention, CNNs, and Neural Tangent Kernels

Analytic Approximation of In-Body Path Loss for Implanted Antennas

Image steganalysis using active learning and hyperparameter optimization

Algorithms push forward the application of MALDI-TOF mass fingerprinting in rapid precise diagnosis

Directly optimizing for synthesizability in generative molecular design using retrosynthesis models

A benchmark dataset for machine learning in ecotoxicology

Principles and Guidelines for Evaluating Social RobotNavigation Algorithms

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Banner Cloud Formation at the Matterhorn: Measurements versus Large-Eddy Simulations

Appropriations and Uses of Travel Time

NORM TORI OF ETALE ALGEBRAS AND UNRAMIFIED BRAUER GROUPS

Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR

A continuum approximation approach to the depot location problem in a crowd-shipping system