Search Results for author:
Found 6 papers, 5 papers with code
Hyperspectral Benchmark: Bridging the Gap between HSI Applications through Comprehensive Dataset and Pretraining
This pretraining regimen serves to enhance the stability of training processes for larger models.
Wavelength-aware 2D Convolutions for Hyperspectral Imaging
Two key challenges are the large channel dimension of the recordings and the incompatibility between cameras of different manufacturers.
Comprehensive Analysis of the Object Detection Pipeline on UAVs
We show that not all parameters have an equal impact on detection accuracy and data throughput, and that by using a suitable compromise between parameters we are able to achieve higher detection accuracy for lightweight object detection models, while keeping the same data throughput.
Tackling the Background Bias in Sparse Object Detection via Cropped Windows
Object detection on Unmanned Aerial Vehicles (UAVs) is still a challenging task.
SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water
Therefore, this paper introduces a large-scaled visual object detection and tracking benchmark (SeaDronesSee) aiming to bridge the gap from land-based vision systems to sea-based ones.
Ranked #1 on
Object Tracking
on SeaDronesSee
Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning
We present a system to measure the ripeness of fruit with a hyperspectral camera and a suitable deep neural network architecture.
