Bio-Inspired Multimodal Imaging in Reduced Visibility

The visual systems found in nature rely on capturing light under different modalities, in terms of spectral sensitivities and polarization sensitivities. Numerous imaging techniques are inspired by this variety, among which, the most famous is color imaging inspired by the trichromacy theory of the human visual system. We investigate the spectral and polarimetric properties of biological imaging systems that will lead to the best performance on scene imaging through haze, i.e., dehazing. We design a benchmark experiment based on modalities inspired by several visual systems, and adapt state-of-the-art image reconstruction algorithms to those modalities. We show the difference in performance of each studied systems and discuss it in front of our methodology and the statistical relevance of our data.

The Science of Visual Data Communication: What Works

Effectively designed data visualizations allow viewers to use their powerful visual systems to understand patterns in data across science, education, health, and public policy. But ineffectively designed visualizations can cause confusion, misunderstanding, or even distrust—especially among viewers with low graphical literacy. We review research-backed guidelines for creating effective and intuitive visualizations oriented toward communicating data to students, coworkers, and the general public. We describe how the visual system can quickly extract broad statistics from a display, whereas poorly designed displays can lead to misperceptions and illusions. Extracting global statistics is fast, but comparing between subsets of values is slow. Effective graphics avoid taxing working memory, guide attention, and respect familiar conventions. Data visualizations can play a critical role in teaching and communication, provided that designers tailor those visualizations to their audience.

Emergence of Lie Symmetries in Functional Architectures Learned by CNNs

In this paper we study the spontaneous development of symmetries in the early layers of a Convolutional Neural Network (CNN) during learning on natural images. Our architecture is built in such a way to mimic some properties of the early stages of biological visual systems. In particular, it contains a pre-filtering step ℓ0 defined in analogy with the Lateral Geniculate Nucleus (LGN). Moreover, the first convolutional layer is equipped with lateral connections defined as a propagation driven by a learned connectivity kernel, in analogy with the horizontal connectivity of the primary visual cortex (V1). We first show that the ℓ0 filter evolves during the training to reach a radially symmetric pattern well approximated by a Laplacian of Gaussian (LoG), which is a well-known model of the receptive profiles of LGN cells. In line with previous works on CNNs, the learned convolutional filters in the first layer can be approximated by Gabor functions, in agreement with well-established models for the receptive profiles of V1 simple cells. Here, we focus on the geometric properties of the learned lateral connectivity kernel of this layer, showing the emergence of orientation selectivity w.r.t. the tuning of the learned filters. We also examine the short-range connectivity and association fields induced by this connectivity kernel, and show qualitative and quantitative comparisons with known group-based models of V1 horizontal connections. These geometric properties arise spontaneously during the training of the CNN architecture, analogously to the emergence of symmetries in visual systems thanks to brain plasticity driven by external stimuli.

Panoramic spatial vision in the bay scallop Argopecten irradians

We have a growing understanding of the light-sensing organs and light-influenced behaviours of animals with distributed visual systems, but we have yet to learn how these animals convert visual input into behavioural output. It has been suggested they consolidate visual information early in their sensory-motor pathways, resulting in them being able to detect visual cues (spatial resolution) without being able to locate them (spatial vision). To explore how an animal with dozens of eyes processes visual information, we analysed the responses of the bay scallop Argopecten irradians to both static and rotating visual stimuli. We found A. irradians distinguish between static visual stimuli in different locations by directing their sensory tentacles towards them and were more likely to point their extended tentacles towards larger visual stimuli. We also found that scallops track rotating stimuli with individual tentacles and with rotating waves of tentacle extension. Our results show, to our knowledge for the first time that scallops have both spatial resolution and spatial vision, indicating their sensory-motor circuits include neural representations of their visual surroundings. Exploring a wide range of animals with distributed visual systems will help us learn the different ways non-cephalized animals convert sensory input into behavioural output.

Synergy of color and motion vision for detecting approaching objects in Drosophila

Color and motion are used by many species to identify salient moving objects. They are processed largely independently, but color contributes to motion processing in humans, for example, enabling moving colored objects to be detected when their luminance matches the background. Here, we demonstrate an unexpected, additional contribution of color to motion vision in Drosophila. We show that behavioral ON-motion responses are more sensitive to UV than for OFF-motion, and we identify cellular pathways connecting UV-sensitive R7 photoreceptors to ON and OFF-motion-sensitive T4 and T5 cells, using neurogenetics and calcium imaging. Remarkably, the synergy of color and motion vision enhances the detection of approaching UV discs, but not green discs with the same chromatic contrast, and we show how this generalizes for visual systems with ON and OFF pathways. Our results provide a computational and circuit basis for how color enhances motion vision to favor the detection of saliently colored objects.

A Spiking Visual Neuron for Depth Perceptual Systems

The biological visual system encodes information into spikes and processes them parallelly by the neural network, which enables the perception with high throughput of visual information processing at an energy budget of a few watts. The parallelism and efficiency of bio-visual system motivates electronic implementation of this biological computing paradigm, which is challenged by the lack of bionic devices, such as spiking neurons that can mimic its biological counterpart. Here, we present a highly bio-realistic spiking visual neuron based on an Ag/TaOX/ITO memristor. Such spiking visual neuron collects visual information by a photodetector, encodes them into action potentials through the memristive spiking encoder, and interprets them for recognition tasks based on a network of neuromorphic transistors. The firing spikes generated by the memristive spiking encoders have a frequency range of 1-200 Hz and sub-micro watts power consumption, very close to the biological counterparts. Furthermore, a spiking visual system is demonstrated, replicating the distance-dependent response and eye fatigue of biological visual systems. The mimicked depth perception shows a recognition improvement by adapting to sights at different distance. Our design presents a fundamental building block for energy-efficient and biologically plausible artificial visual systems.

Special Somatic Sensory Afferent Systems Overview

The special somatic sensory afferent systems include the auditory, vestibular, and visual systems. Auditory and vestibular afferent information is received by cranial nerve VIII, which projects to central pathways. Cranial nerve II carries afferent visual information to central pathways. This chapter reviews the receptors and structural components of these special somatic sensory afferent systems. The ossicular chain (malleus, incus, and stapes) within the air-filled middle ear serves as a transformer that bridges the impedance mismatch between sound vibrations in air on the large tympanic membrane and the resulting vibrations onto the small stapedial footplate.

IMPLEMENTASI METODE DMAIC (DEFINE, MEASURE,ANALYZE, IMPROVE, CONTROL) UNTUK MENURUNKAN CACAT BONDING SEPATU DI GEDUNG 2 (DUA) PADA PT. PARKLAND WORLD INDONESIA

This study focuses on how to control defective products at PT. Parkland World Indonesia, a company engaged in the Adidas brand shoe industry for the period April 2020 to March 2021, the average product achievement reaches 8.37%, while the company wants Zero Defect. The purpose of this study is to reduce bond defects through an approximation approach, where we observe and conduct tests in order to improve performance and reduce. The method to guarantee the quality of the product produced is DMAIC (Define, Measure, Analyze, Improve, Control) which is a data-based problem solving approach that helps to optimally correct defects caused by the production process can decrease. The results of the analyzed data showed 5 CTQ (Critical to Quality) bonds with the highest percentage of bonding stabilizer at 43.70%. The conclusions and recommendations that can be drawn from this study are the causes of shoe ties that can be prevented by implementing several proposed improvements, by providing the latest SOPs, maximum WIP visual standards, brush change visual systems, and providing RCA (root cause analysis) board meetings

Seeing the world through the eyes of a butterfly: visual ecology of the territorial males of Pararge aegeria (Lepidoptera: Nymphalidae)

Combining studies of animal visual systems with exact imaging of their visual environment can get us a step closer to understand how animals see their “Umwelt”. Here, we have combined both methods to better understand how males of the speckled wood butterfly, Pararge aegeria, see the surroundings of their perches. These males are well known to sit and wait for a chance to mate with a passing females, in sunspot territories in European forests. We provide a detailed description of the males' body and head posture, viewing direction, visual field and spatial resolution, as well as the visual environment. Pararge aegeria has sexually dimorphic eyes, the smallest interommatidial angles of males are around 1°, those of females 1.5°. Perching males face the antisolar direction with their retinal region of the highest resolution pointing at an angle of about 45° above the horizon; thus, looking at a rather even and dark background in front of which they likely have the best chance to detect a sunlit female passing through the sunspot.