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Strong gravitational lensing is a promising probe of the substructure of dark matter halos. Deep learning methods have the potential to accurately identify images containing substructure, and differentiate WIMP dark matter from other well…
Computer vision techniques are on the rise for industrial applications, like process supervision and autonomous agents, e.g., in the healthcare domain and dangerous environments. While the general usability of these techniques is high,…
Polarization is a fundamental property of light that carries distinct and valuable information. Consequently, its precise measurement is crucial for numerous applications, including biomedical imaging, remote sensing, and optical…
Significance: The depolarization of circularly polarized light caused by scattering in turbid media reveals structural information about the dispersed particles, such as their size, density, and distribution, which is useful for…
There is a high demand for fully automated methods for the analysis of primary particle size distributions of agglomerated, sintered or occluded primary particles, due to their impact on material properties. Therefore, a novel, deep…
As an essential attribute of organic compounds, polarity has a profound influence on many molecular properties such as solubility and phase transition temperature. Thin layer chromatography (TLC) represents a commonly used technique for…
The increasing prevalence of marine pollution during the past few decades motivated recent research to help ease the situation. Typical water quality assessment requires continuous monitoring of water and sediments at remote locations with…
Histopathological characterization of colorectal polyps is an important principle for determining the risk of colorectal cancer and future rates of surveillance for patients. This characterization is time-intensive, requires years of…
The problem of segregating recyclable waste is fairly daunting for many countries. This article presents an approach for image based classification of plastic waste using one-shot learning techniques. The proposed approach exploits…
Advances in vectorial polarisation-resolved imaging are bringing new capabilities to applications ranging from fundamental physics through to clinical diagnosis. Imaging polarimetry requires determination of the Mueller matrix (MM) at every…
The development of robust, real-time optical methods for the detection and tracking of particles in complex multiple scattering media is a problem of practical importance in a number of fields, including environmental monitoring, air…
A very efficient method for the calculation of the effective optical response of nano-structured composite systems allows the design of metamaterials tailored for specific optical polarization properties. We use our method to design 2D…
Plastic waste in aquatic environments poses severe risks to marine life and human health. Autonomous robots can be utilized to collect floating waste, but they require accurate object identification capability. While deep learning has been…
Chemicals released in the air can be extremely dangerous for human beings and the environment. Hyperspectral images can be used to identify chemical plumes, however the task can be extremely challenging. Assuming we know a priori that some…
Accurate detection and analysis of traces of persistent organic pollutants in water is important in many areas, including environmental monitoring and food quality control, due to their long environmental stability and potential…
Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution and the Bayesian posterior. Such an approximation leads to severe mode collapse and…
The real-time, in-line analysis of light polarization is critical in optical communication networks, which suffers from the complex systems with numerous bulky opto-electro-mechanical elements tandemly arranged along optical path. Here, we…
The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from various sources and setups. Here, state-of-the-art machine…
The polarimetry of the light scattered by planetary surfaces is a powerful tool to provide constraints on their microstructure. To improve the interpretation of polarimetric data from icy surfaces, we have developed the POLarimeter for ICE…
This paper proposes a probabilistic deep metric learning (PDML) framework for hyperspectral image classification, which aims to predict the category of each pixel for an image captured by hyperspectral sensors. The core problem for…