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Leveraging Remote Sensing Data for Yield Prediction with Deep Transfer Learning

Sensors (Basel, Switzerland), 2024-01, Vol.24 (3), p.770

2024

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Deep Interpolation of Remote Sensing Land Surface Temperature Data with Partial Convolutions

Sensors (Basel, Switzerland), 2024-02, Vol.24 (5), p.1604

2024

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The Potential of Diffusion-Based Near-Infrared Image Colorization

Sensors (Basel, Switzerland), 2024-02, Vol.24 (5), p.1565

2024

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Image-Based Automated Species Identification: Can Virtual Data Augmentation Overcome Problems of Insufficient Sampling?

Systematic biology, 2022-02, Vol.71 (2), p.320-333

2022

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Image-based species identification of wild bees using convolutional neural networks

Ecological informatics, 2020-01, Vol.55, p.101017, Article 101017

2020

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Conditional Feature Selection: Evaluating Model Averaging When Selecting Features with Shapley Values

Geomatics (Basel), 2024-09, Vol.4 (3), p.286-310

2024

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SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision

Sensors (Basel, Switzerland), 2022-11, Vol.22 (23), p.9082

2022

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High-Precision Phenotyping of Grape Bunch Architecture Using Fast 3D Sensor and Automation

Sensors (Basel, Switzerland), 2018-03, Vol.18 (3), p.763

2018

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Automated 3D reconstruction of grape cluster architecture from sensor data for efficient phenotyping

Computers and electronics in agriculture, 2015-06, Vol.114, p.163-177

2015

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Identification of animals and recognition of their actions in wildlife videos using deep learning techniques

Ecological informatics, 2021-03, Vol.61, p.101215, Article 101215

2021

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Action Detection for Wildlife Monitoring with Camera Traps Based on Segmentation with Filtering of Tracklets (SWIFT) and Mask-Guided Action Recognition (MAROON)

Applied sciences, 2024-01, Vol.14 (2), p.514

2024

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A semi‐automated camera trap distance sampling approach for population density estimation

Remote sensing in ecology and conservation, 2024-04, Vol.10 (2), p.156-171

2024

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Automated Visual Large Scale Monitoring of Faunal Biodiversity

Pattern recognition and image analysis, 2021-07, Vol.31 (3), p.477-488

2021

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Relieving the Phenotyping Bottleneck for Grape Bunch Architecture in Grapevine Breeding Research: Implementation of a 3D-Based Phenotyping Approach for Quantitative Trait Locus Mapping

Horticulturae, 2022-10, Vol.8 (10), p.907

2022

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Wildlife 3D multi-object tracking

Ecological informatics, 2022-11, Vol.71, p.101790, Article 101790

2022

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Instance segmentation and tracking of animals in wildlife videos: SWIFT - segmentation with filtering of tracklets

Ecological informatics, 2022-11, Vol.71, p.101794, Article 101794

2022

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Identification of Africanized honey bees through wing morphometrics: two fast and efficient procedures

Apidologie, 2008-09, Vol.39 (5), p.488-494

2008

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Improving wildlife tracking using 3D information

Ecological informatics, 2022-05, Vol.68, p.101535, Article 101535

2022

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Saving costs for video data annotation in wildlife monitoring

Ecological informatics, 2021-11, Vol.65, p.101418, Article 101418

2021

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Extreme Gradient Boosting for yield estimation compared with Deep Learning approaches

Computers and electronics in agriculture, 2022-11, Vol.202, p.107346, Article 107346

2022

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On the extraction and relevance ranking of visual morphological traits for taxon identification

Ecological informatics, 2020-11, Vol.60, p.101138, Article 101138

2020

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Automated distance estimation for wildlife camera trapping

Ecological informatics, 2022-09, Vol.70, p.101734, Article 101734

2022

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LeafNet: A computer vision system for automatic plant species identification

Ecological informatics, 2017-07, Vol.40, p.50-56

2017

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High-precision 3D detection and reconstruction of grapes from laser range data for efficient phenotyping based on supervised learning

Computers and electronics in agriculture, 2017-04, Vol.135, p.300-311

2017

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Leveraging Remote Sensing Data for Yield Prediction with Deep Transfer Learning

Deep Interpolation of Remote Sensing Land Surface Temperature Data with Partial Convolutions

The Potential of Diffusion-Based Near-Infrared Image Colorization

Image-Based Automated Species Identification: Can Virtual Data Augmentation Overcome Problems of Insufficient Sampling?

Image-based species identification of wild bees using convolutional neural networks

Conditional Feature Selection: Evaluating Model Averaging When Selecting Features with Shapley Values

SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision

High-Precision Phenotyping of Grape Bunch Architecture Using Fast 3D Sensor and Automation

Automated 3D reconstruction of grape cluster architecture from sensor data for efficient phenotyping

Towards a multisensor station for automated biodiversity monitoring

Identification of animals and recognition of their actions in wildlife videos using deep learning techniques

Action Detection for Wildlife Monitoring with Camera Traps Based on Segmentation with Filtering of Tracklets (SWIFT) and Mask-Guided Action Recognition (MAROON)

A semi‐automated camera trap distance sampling approach for population density estimation

Automated Visual Large Scale Monitoring of Faunal Biodiversity

Relieving the Phenotyping Bottleneck for Grape Bunch Architecture in Grapevine Breeding Research: Implementation of a 3D-Based Phenotyping Approach for Quantitative Trait Locus Mapping

Wildlife 3D multi-object tracking

Instance segmentation and tracking of animals in wildlife videos: SWIFT - segmentation with filtering of tracklets

Identification of Africanized honey bees through wing morphometrics: two fast and efficient procedures

Improving wildlife tracking using 3D information

Saving costs for video data annotation in wildlife monitoring

Extreme Gradient Boosting for yield estimation compared with Deep Learning approaches

On the extraction and relevance ranking of visual morphological traits for taxon identification

Automated distance estimation for wildlife camera trapping

LeafNet: A computer vision system for automatic plant species identification

High-precision 3D detection and reconstruction of grapes from laser range data for efficient phenotyping based on supervised learning

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