168 citations · 170 across the 8 of their papers we have counts for
8 papers
MWIR-4-Plastic: The Identification of Complex End-of-Life Industrial Plastic using Mid-wave Infrared Hyperspectral Imaging and Machine Learning
Elias Arbash, Andréa de Lima Ribeiro, Filipa Simões +9
The automated sorting of shredded black plastics from end-of-life (EOF) industrial waste presents a significant challenge in recycling facilities, primarily due to the limitations…
MiSiSUn: Minimum Simplex Semisupervised Unmixing
Behnood Rasti, Bikram Koirala, Paul Scheunders
This paper proposes a semisupervised geometric unmixing approach called minimum simplex semisupervised unmixing (MiSiSUn). The geometry of the data was incorporated for the first t…
Electrolyzers-HSI: Close-Range Multi-Scene Hyperspectral Imaging Benchmark Dataset
Elias Arbash, Ahmed Jamal Afifi, Ymane Belahsen +4
The global challenge of sustainable recycling demands automated, fast, and accurate, state-of-the-art (SOTA) material detection systems that act as a bedrock for a circular economy…
A Tractable Two-Step Linear Mixing Model Solved with Second-Order Optimization for Spectral Unmixing under Variability
Xander Haijen, Bikram Koirala, Xuanwen Tao +1
In this paper, we propose a Two-Step Linear Mixing Model (2LMM) that bridges the gap between model complexity and computational tractability. The model achieves this by introducing…
A Multisensor Hyperspectral Benchmark Dataset For Unmixing of Intimate Mixtures
Bikram Koirala, Behnood Rasti, Zakaria Bnoulkacem +11
Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differe…
Corrosion Monitoring On Zinc Electroplated Steel Using Shortwave Infrared Hyperspectral Imaging
Thomas De Kerf, Zohreh Zahiri, Paul Scheunders +1
In this study, we investigate the use of hyperspectral imaging (HSI) to inspect the formation of corrosion products on galvanised carbon steel samples. Ten samples were subjected t…
Deep Hyperspectral Unmixing using Transformer Network
Preetam Ghosh, Swalpa Kumar Roy, Bikram Koirala +2
Currently, this paper is under review in IEEE. Transformers have intrigued the vision research community with their state-of-the-art performance in natural language processing. Wit…
Imprecise k-space sampling and central brightening
R. A. Hanel, S. De Backer, J. Sijbers +1
In real-world sampling of k-space data, one generally makes a stochastic error not only in the value of the sample but in the effective position of the drawn sample. We refer to th…