Alexander Bucksch

Drought-Spec-Net: Early Tomato Drought Detection and Potential Yield-Impact Assessment Using Vis NIR Data

This paper develops Drought-Spec-Net, a model for early tomato drought detection using Vis NIR data, achieving high accuracy and providing yield impact assessments.

DIRTNet: Enabling Root Phenotyping with Fiber Bragg Grating Sensors

DIRTNet, a hybrid deep learning model, accurately predicts root depth and diameter from FBG sensor data in both simulated and real maize root growth scenarios.

Optimizing root phenotyping: Assessing the impact of camera calibration on 3D root reconstruction

This study evaluates how camera calibration affects 3D root reconstruction quality and finds that proper calibration significantly improves model accuracy over post-processing filtering.

LeafyResNet: Fusarium Wilt Detection in Lettuce Using UAV RGB Imaging and Advanced Deep Learning Model

This paper develops LeafyResNet, a deep learning model for detecting Fusarium wilt in lettuce using UAV RGB imaging, achieving high accuracy and precision.

Fiber Bragg grating based sensing system for non-destructive root phenotyping using ResNet prediction

This paper develops a fiber Bragg grating sensing system with ResNet models to predict root width and depth in real-time, achieving high accuracy in pseudo-root measurements.