Classifying vocal responses of broilers to environmental stressors via artificial neural network.

Detecting early-stage stress in broiler farms is crucial for optimising growth rates and animal well-being. This study aims to classify various stress calls in broilers exposed to cold, heat, or wind, using acoustic signal processing and a transformer artificial neural network (ANN). Two consecutive trials were conducted with varying amounts of collected data, and three ANN models with the same architecture but different parameters were examined.

Simulating a turbulent video affected by spatiotemporally varying blur and tilt using temporal cross correlation of intermodal Zernike coefficients.

Videos captured in long-distance horizontal imaging through the atmosphere suffer from dynamic spatiotemporal movements and blur caused by the air turbulence. Simulations of atmospheric turbulence in such videos, which have been conducted in the past, are difficult to compute. Our goal in this research is to develop an effective simulation algorithm of videos affected by atmospheric turbulence characterized by spatiotemporally varying blur and tilt, when supplied with a given image.

Emotion Classification Based on Pulsatile Images Extracted from Short Facial Videos via Deep Learning.

Most human emotion recognition methods largely depend on classifying stereotypical facial expressions that represent emotions. However, such facial expressions do not necessarily correspond to actual emotional states and may correspond to communicative intentions. In other cases, emotions are hidden, cannot be expressed, or may have lower arousal manifested by less pronounced facial expressions, as may occur during passive video viewing.

Biometric identification of dairy cows via real-time facial recognition.

Biometrics methods, which currently identify humans, can potentially identify dairy cows. Given that animal movements cannot be easily controlled, identification accuracy and system robustness are challenging when deploying an animal biometrics recognition system on a real farm. Our proposed method performs multiple-cow face detection and face classification from videos by adjusting recent state-of-the-art deep-learning methods.

Atmospheric Turbulence Degraded Video Restoration with Recurrent GAN (ATVR-GAN).

Atmospheric turbulence (AT) can change the path and direction of light during video capturing of a target in space due to the random motion of the turbulent medium, a phenomenon that is most noticeable when shooting videos at long ranges, resulting in severe video dynamic distortion and blur. To mitigate geometric distortion and reduce spatially and temporally varying blur, we propose a novel Atmospheric Turbulence Video Restoration Generative Adversarial Network (ATVR-GAN) with a specialized Recurrent Neural Network (RNN) generator, which is trained to predict the scene's turbulent optical flow (OF) field and utilizes a recurrent structure to catch both spatial and temporal dependencies. The new architecture is trained using a newly combined loss function that counts for the spatiotemporal distortions, specifically tailored to the AT problem.

3D Object Detection via 2D Segmentation-Based Computational Integral Imaging Applied to a Real Video.

This study aims to achieve accurate three-dimensional (3D) localization of multiple objects in a complicated scene using passive imaging. It is challenging, as it requires accurate localization of the objects in all three dimensions given recorded 2D images. An integral imaging system captures the scene from multiple angles and is able to computationally produce blur-based depth information about the objects in the scene.

Turbulence video simulation using the spatiotemporal cross correlation of distortion fields.

Previous simulations of atmospheric turbulence in videos are computationally complex. The purpose of this study is to develop an efficient algorithm for simulating spatiotemporal videos affected by atmospheric turbulence, given a static image. We extend an existing method for the simulation of atmospheric turbulence in a single image by incorporating turbulence properties in the time domain and the blurring effect.

Fast and Enhanced MMW Imaging System Using a Simple Row Detector Circuit with GDDs as Sensor Elements and an FFT-Based Signal Acquisition System.

The relatively high atmospheric propagation of millimeter-waves (MMW) was found to be one of the most critical reasons for the development of reliable sensors for MMW detection. According to previous research works, it has been already shown that incident MMW radiation on a glow discharge detector (GDD) can increase the discharge current. Hence, the electrical mode of detection can be employed to detect the presence of MMW radiation.

A Machine Learning Approach to Design of Aperiodic, Clustered-Dot Halftone Screens via Direct Binary Search.

Aperiodic, clustered-dot, halftone patterns have recently become popular for commercial printing of continuous-tone images with laser, electrophotographic presses, because of their inherent stability and resistance to moiré artifacts. Halftone screens designed using the multistage, multipass, clustered direct binary search (MS-MP-CLU-DBS) algorithm can yield halftone patterns with very high visual quality. But the characteristics of these halftone patterns depend on three input parameters for which there are no known formulas to choose their values to yield halftone patterns of a certain quality level and scale.

Classification of emotional states via transdermal cardiovascular spatiotemporal facial patterns using multispectral face videos.

We describe a new method for remote emotional state assessment using multispectral face videos, and present our findings: unique transdermal, cardiovascular and spatiotemporal facial patterns associated with different emotional states. The method does not rely on stereotypical facial expressions but utilizes different wavelength sensitivities (visible spectrum, near-infrared, and long-wave infrared) to gauge correlates of autonomic nervous system activity spatially and temporally distributed across the human face (e.g.

Simulating the perceptual effects of electrode-retina distance in prosthetic vision.

. Retinal prostheses aim to restore some vision in retinitis pigmentosa and age-related macular degeneration blind patients. Many spatial and temporal aspects have been found to affect prosthetic vision.

Retinal prosthetic vision simulation: temporal aspects.

. The perception of individuals fitted with retinal prostheses is not fully understood, although several retinal implants have been tested and commercialized. Realistic simulations of perception with retinal implants would be useful for future development and evaluation of such systems.

A machine vision system to detect and count laying hens in battery cages.

Manually counting hens in battery cages on large commercial poultry farms is a challenging task: time-consuming and often inaccurate. Therefore, the aim of this study was to develop a machine vision system that automatically counts the number of hens in battery cages. Automatically counting hens can help a regulatory agency or inspecting officer to estimate the number of living birds in a cage and, thus animal density, to ensure that they conform to government regulations or quality certification requirements.

New Design for Compact Color Screen Sets for High-End Digital Color Press.

Digital halftoning is an essential part of the process for printing color, continuous-tone content. Traditionally, the highest quality has been achieved with analog, offset lithographic presses, using color screen sets that yield periodic, clustereddot halftone patterns. Increasingly, these systems are being supplanted by digital presses that are based on either electrophotographic or inkjet marking processes.

Ultra-wideband and inexpensive glow discharge detector for millimeter-wave wireless communication based on upconversion to visual light.

Data traffic is increasing rapidly, especially on wireless channels, pushing the carrier frequency to the X, K, and millimeter-wave (MMW) bands. This requires development of new technologies and communication components operating at those bands. The detectors and receivers for those bands are very expensive, have high sensitivity to electrostatic discharge, and can be damaged by high incident power.

Pulse Oximetry with Two Infrared Wavelengths without Calibration in Extracted Arterial Blood.

Oxygen saturation in arterial blood (SaO₂) provides information about the performance of the respiratory system. Non-invasive measurement of SaO₂ by commercial pulse oximeters (SpO₂) make use of photoplethysmographic pulses in the red and infrared regions and utilizes the different spectra of light absorption by oxygenated and de-oxygenated hemoglobin. Because light scattering and optical path-lengths differ between the two wavelengths, commercial pulse oximeters require empirical calibration which is based on SaO₂ measurement in extracted arterial blood.

Effects of elemental images' quantity on three-dimensional segmentation using computational integral imaging: publisher's note.

This publisher's note corrects the Funding section in Appl. Opt.56, 2132 (2017)APOPAI0003-693510.

Optimized depth of field methodology using annular liquid crystal modulator assisted by image processing.

An optical-digital tunable depth of field (DOF) methodology is presented. The suggested methodology forms a fused image based on the sharpest similar depth regions from a set of source images taken with different phase masks. Each phase mask contains a different degree of DOF extension and is implemented by using an annular liquid crystal spatial light modulator, which consists of 16-ring electrodes positioned in the pupil plane.

Effects of elemental images' quantity on three-dimensional segmentation using computational integral imaging.

3D object detection and isolation can be achieved algorithmically using computational integral-imaging data. The 3D scene is acquired by a multi-channel system, where each channel (elemental image) captures the scene from a shifted perspective angle. The number of these channels affects the weight, the cost, and the computational load of the segmentation process, while a lower number of channels may reduce the performance of the objects' separation in the 3D scene.

Automatic 3D object localization and isolation using computational integral imaging.

Detecting objects in three-dimensional (3D) space may be useful for various applications. We present a method to detect the 3D locations of objects using computationally reconstructed images obtained by integral imaging. The new algorithm exploits the space-variant blurring properties of the reconstructed images to detect and isolate objects at their depth locations, while removing traces of objects from other depths.

Capability of long distance 100 GHz FMCW using a single GDD lamp sensor.

Millimeter wave (MMW)-based imaging systems are required for applications in medicine, homeland security, concealed weapon detection, and space technology. The lack of inexpensive room temperature imaging sensors makes it difficult to provide a suitable MMW system for many of the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector.

Spatial-phase-shift imaging interferometry using a spectrally modulated white light source.

An extension of the white light spatial-phase-shift (WLSPS) for object surface measurements is described. Using WLSPS, surface measurements can be obtained from any real object image without the need of a reference beam, thus achieving inherent vibration cancellation. The surface topography is obtained by acquiring multiple images of an object illuminated by a spectrally modulated white light source and using an appropriate algorithm.

Active confocal imaging for visual prostheses.

There are encouraging advances in prosthetic vision for the blind, including retinal and cortical implants, and other "sensory substitution devices" that use tactile or electrical stimulation. However, they all have low resolution, limited visual field, and can display only few gray levels (limited dynamic range), severely restricting their utility. To overcome these limitations, image processing or the imaging system could emphasize objects of interest and suppress the background clutter.