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 ...

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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 ...

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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 ...

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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