Jakob Juul Larsen

Aarhus University

Denmark

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Articles (20)

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2025

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2022

Collaborators (6)

Anders Vest Christiansen

Professor

Aarhus University

DENMARK

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Esben Auken

Aarhus University

DENMARK

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Mike Müller-Petke

Professor

Leibniz University Hannover

GERMANY

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Denys Grombacher

Assistant Professor

Aarhus University

DENMARK

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Muhammad Rizwan Asif

Aarhus University

DENMARK

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Nikhil Gaikwad

Aarhus University

DENMARK

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Jakob Juul Larsen

Research Interests

Contact this professor

Articles (20)

Comparative analysis of deep learning and traditional airborne electromagnetic data processing: A case study

Efficient mapping of complex groundwater systems associated with braided rivers using small coil surface nuclear magnetic resonance

An efficient cross-borehole direct current resistivity monitoring instrument

A high-duty-cycle transmitter unit for steady-state surface NMR instruments

An investigation of factors affecting the depths of steady-state surface nuclear magnetic resonance signals

Observation of spikelets in steady-state surface nuclear magnetic resonance data

Ground‐Truth Validation of T2 ${T}_{2}$ Estimates From Steady‐State Surface NMR

Feasibility of Surface Nuclear Magnetic Resonance With Absurdly Long Excitation Pulses

An optimized and hybrid gating scheme for the suppression of very low-frequency radios in transient electromagnetic systems

Observation of spikelets in steady-state surface nuclear magnetic resonance data

Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance – three Danish case studies

A surface NMR forward in a dot product

Signal Processing Steady-State Surface NMR Data

DL-RMD: a geophysically constrained electromagnetic resistivity model database (RMD) for deep learning (DL) applications

DL-RMD: a geophysically constrained electromagnetic resistivity model database for deep learning applications

Review of Acquisition and Signal Processing Methods for Electromagnetic Noise Reduction and Retrieval of Surface Nuclear Magnetic Resonance Parameters

Integrating neural networks in least-squares inversion of airborne time-domain electromagnetic data

Frequency Shifting Steady‐State Surface NMR Signals to Avoid Problematic Narrowband‐Noise Sources

Efficient processing of surface NMR data with spectral analysis

A Neural Network-Based Hybrid Framework for Least-Squares Inversion of Transient Electromagnetic Data

Collaborators (6)

Anders Vest Christiansen

Esben Auken

Mike Müller-Petke

Denys Grombacher

Muhammad Rizwan Asif

Nikhil Gaikwad

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