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Automation in agriculture plays a vital role in addressing challenges related to crop monitoring and disease management, particularly through early detection systems. This study investigates the effectiveness of combining multimodal Large…
This paper presents an approach developed to address the PlantClef 2025 challenge, which consists of a fine-grained multi-label species identification, over high-resolution images. Our solution focused on employing class prototypes obtained…
Common remote sensing modalities (RGB, multispectral, hyperspectral imaging or LiDAR) are often used to indirectly measure crop health and do not directly capture plant stress indicators. Commercially available direct leaf sensors are…
Large-scale particle physics detectors often contain millions of repeated components, making precise and efficient quality control essential. We have developed a semiautomatic system for dimensional screening of 1 cm$^3$ plastic…
Most detector systems used for positron emission particle tracking (PEPT) are very expensive due to the use of inorganic plastic scintillators combined with a high number of readout electronic channels. This work aims to reduce the overall…
The purpose of the Insect Detection System for Crop and Plant Health is to keep an eye out for and identify insect infestations in farming areas. By utilizing cutting-edge technology like computer vision and machine learning, the system…
An accurate and timely detection of diseases and pests in rice plants can help farmers in applying timely treatment on the plants and thereby can reduce the economic losses substantially. Recent developments in deep learning based…
Photon counting CT (PCCT) has been a research focus in the last two decades. Recent studies and advancements have demonstrated that systems using semiconductor-based photon counting detectors (PCDs) have the potential to provide better…
Automated segmentation of cancerous lesions in PET/CT scans is a crucial first step in quantitative image analysis. However, training deep learning models for segmentation with high accuracy is particularly challenging due to the variations…
The TT-PET collaboration is developing a PET scanner for small animals with 30 ps time-of-flight resolution and sub-millimetre 3D detection granularity. The sensitive element of the scanner is a monolithic silicon pixel detector based on…
We report a theoretical study of clusters of evanescently-coupled 2D whispering-gallery (WG) mode optical micro-cavities (termed "photonic molecules") as chemosensing and biosensing platforms. Photonic molecules (PMs) supporting modes with…
Automated analysis of high-resolution transmission electron microscopy (HRTEM) images is increasingly essential for advancing research in organic electronics, where precise characterization of nanoscale crystal structures is crucial for…
In positron emission tomography (PET), a clear theoretical model describing how system sensitivity varies as a source is moved trans-axially within the field of view (FOV) is lacking. The current understanding and practical intuition often…
We present ground-based infrared transit observations for four dynamically interacting \textit{Kepler} planets, including Kepler-29b, Kepler-36c, KOI-1783.01, and Kepler-177c, obtained using the Wide-field Infrared Camera on the Hale 200"…
Resistive Plate Chambers (RPCs) featuring 1 mm gas volumes combined with high-pressure phenolic laminate (HPL) electrodes provide excellent timing resolution down to a few hundred picoseconds, along with spatial resolution on the order of a…
The measurement of environmental neutrons is particularly important in the search for new physics, such as dark matter particles, because neutrons constitute an often-irreducible background source. The measurement of the neutron energy…
Particle beams focused to micrometer-sized spots play a crucial role in forefront research using low-energy positrons. Their expedient and wide application, however, requires highly-resolved, fast beam diagnostics. We have developed two…
A new type of gaseous micropattern particle detector based on a closed-cell microcavity plasma panel sensor is reported. The first device was fabricated with 1 x 1 x 2 mm cells. It has shown very clean signals of 0.6 to 2.5 volt amplitude,…
Diffusion models have shown great promise in medical image denoising and reconstruction, but their application to Positron Emission Tomography (PET) imaging remains limited by tracer-specific contrast variability and high computational…
This study proposes a deep learning-based framework for automated segmentation of brain regions and classification of amyloid positivity using positron emission tomography (PET) images alone, without the need for structural MRI or CT. A 3D…