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Humans can robustly recognize and localize objects by integrating visual and auditory cues. While machines are able to do the same now with images, less work has been done with sounds. This work develops an approach for dense semantic…

This work presents a unified framework for estimating both sound-field direction and diffuseness using practical microphone arrays with different spatial configurations. Building on covariance-based diffuseness models, we formulate a…

This paper proposes a polyline shaped array based system scheme, associated with mechanical scanning along the perpendicular direction of the array, for near-field millimeter-wave (MMW) imaging. Each section of the polyline is a chord of a…

A resonance detection scheme and some useful ideas for cavity-based searches of light cold dark matter particles (such as axions) are presented, as an effort to aid in the on-going endeavors in this direction as well as for future…

There is a great desire to extend ultrasonic techniques to the imaging and characterization of nanoobjects. This can be achieved by picosecond ultrasonics, where by using ultrafast lasers it is possible to generate and detect acoustic waves…

Pathological anomalies exhibit diverse appearances in medical imaging, making it difficult to collect and annotate a representative amount of data required to train deep learning models in a supervised setting. Therefore, in this work, we…

Hyperspectral imaging provides spatially resolved spectral information. Utilising dual frequency combs as active illumination sources, hyperspectral imaging with ultra-high spectral resolution can be implemented in a scan-free manner when a…

Doppler echocardiography offers critical insights into cardiac function and phases by quantifying blood flow velocities and evaluating myocardial motion. However, previous methods for automating Doppler analysis, ranging from initial signal…

In industry, machine anomalous sound detection (ASD) is in great demand. However, collecting enough abnormal samples is difficult due to the high cost, which boosts the rapid development of unsupervised ASD algorithms. Autoencoder (AE)…

Ultrasound images are one of the most widely used techniques in clinical settings to analyze and detect different organs for study or diagnoses of diseases. The dependence on subjective opinions of experts such as radiologists calls for an…

Echocardiography has been a prominent tool for the diagnosis of cardiac disease. However, these diagnoses can be heavily impeded by poor image quality. Acoustic clutter emerges due to multipath reflections imposed by layers of skin,…

The active element pattern method is widely employed in beam pattern synthesis of array antenna to account for mutual coupling between antenna elements. Calculating the active element patterns for large number of array requires full-wave…

This paper considers a compressive multi-spectral light field camera model that utilizes a one-hot spectralcoded mask and a microlens array to capture spatial, angular, and spectral information using a single monochrome sensor. We propose a…

Binary change detection in bi-temporal co-registered hyperspectral images is a challenging task due to a large number of spectral bands present in the data. Researchers, therefore, try to handle it by reducing dimensions. The proposed work…

Ultrasound (US) image segmentation is an active research area that requires real-time and highly accurate analysis in many scenarios. The detect-to-segment (DTS) frameworks have been recently proposed to balance accuracy and efficiency.…

Medical instrument detection is essential for computer-assisted interventions since it would facilitate the surgeons to find the instrument efficiently with a better interpretation, which leads to a better outcome. This article reviews…

We demonstrate practically approximation-free electrostatic calculations of micromesh detectors that can be extended to any other type of micropattern detectors. Using newly developed Boundary Element Method called Robin Hood Method we can…

The success of deep learning methods relies on the availability of a large number of datasets with annotations; however, curating such datasets is burdensome, especially for medical images. To relieve such a burden for a landmark detection…

As both computer vision models and biomedical datasets grow in size, there is an increasing need for efficient inference algorithms. We utilize cascade detectors to efficiently identify sparse objects in multiresolution images. Given an…

To address the increasingly serious issue of noise pollution, we propose an ultra-broadband and wide-angle acoustic absorber based on a periodic acoustic rigid-metaporous composite array. Numerical simulation results verify the broadband…