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Abandoned houses have become a common feature of the local landscapes: the rising number of abandoned houses is a major challenge facing many counties in South Korea. Their presence negatively influences the neighborhood by undermining its aesthetic quality, depreciating the perception of safety in the neighborhood properties, and deepening the fiscal deficit of local financing. The detection of abandoned houses is the first step toward adequate housing management by local governments. This study aims to provide a cost-effective and prompt approach to identifying abandoned houses in rural areas. Multi-source data, that is, images and building registry data are utilized and a multi-input neural network is designed to adopt these heterogeneous datasets. Trained by the two source datasets, the proposed network achieves 86.2% accuracy in classifying abandoned houses, which is an acceptable performance level in administrative practice. The database of abandoned houses identified in this manner is expected to promote effective housing management by governments and ultimately contribute to mitigating vacancies in rural areas.

Abstract The effective integration of RGB and depth map features to improve the performance of RGB‐D salient object detection (SOD) has garnered significant research interest. The existing dual‐stream models can be used for high‐level feature fusion or unidirectionally transferring depth features to RGB features; however, they are unable to fully exploit the differences in modality. Furthermore, owing to the influence of image background information, the generated salient object is affected by background swallow. Herein, a three‐stream RGB‐D SOD method based on cross‐layer and cross‐modal dual‐attention (CMDA) fusion is proposed. In the encoding stage, the CMDA fusion module is used to fuse RGB and depth features layer by layer. Through this module, merged interactive features may be used to extract the richer features of salient objects, realize the commonality and complementarity of fusion features, and achieve effective cross‐modal fusion. In addition, for the decoding stage, a cross‐level feature fusion module that introduces global context features into the up‐sampling process, reduces the impact of salient objects being swallowed by the background, and helps to accurately detect salient areas is proposed. Three different branch features are used for simultaneous end‐to‐end training. The experimental results demonstrate that the proposed method outperforms other methods in terms of multiple evaluation metrics on four datasets. Furthermore, the authors visualize the precision–recall curve, F‐measure curve, and saliency map, which indicate that the detection effect of the proposed method is superior to those of other methods. During the testing stage, our model ran at 14 frames per second (FPS).

Similarly to China, Japan has a long history of worshiping fortune gods. The act of making offerings and praying to these deities has been practiced since ancient times. Fortune gods are figures in Japanese folk religion that are believed to bring happiness, hope, and good luck. When speaking of fortune gods in Japan, people will first think of the Seven Lucky Gods. Apart from them, there are also some local fortune gods such as Fukusuke and Sendai Shiro. These gods share some common traits and also have connections with the Japanese folk belief in Fukuko (fortune child). This study adopts a comparative methodology to compare Japan’s Seven Lucky Gods with the local Japanese fortune gods as well as Fukuko, and then analyze their similarities. This article argues that the Japanese fortune gods have two major common characteristics: the super power to bring good fortune, and their distinctive appearance. By systematically analyzing the common features of Japanese fortune gods, this study will clarify the mechanism behind their deification as fortune deities and also help us to gain a better insight into the Japanese conceptions of deities and spirits.

Over the past few decades, there has been a notable surge in interest in green stormwater infrastructure (GSI). This trend is a result of the need to effectively address issues related to runoff, pollution, and the adverse effects of urbanization and impervious surfaces on waterways. Concurrently, umanned aerial vehicles (UAVs) have gained prominence across applications, including photogrammetry, military applications, precision farming, agricultural land, forestry, environmental surveillance, remote-sensing, and infrastructure maintenance. Despite the widespread use of GSI and UAV technologies, there remains a glaring gap in research focused on the evaluation and maintenance of the GSIs using UAV-based imagery. This study aimed to develop an integrated framework to evaluate plant density and health within GSIs using UAV-based imagery. This integrated framework incorporated the UAV (commonly known as a drone), WebOpenDroneMap (WebDOM), ArcMap, PyCharm, and the Canopeo application. The UAV-based images of GSI components, encompassing trees, grass, soil, and unhealthy trees, as well as entire GSIs (e.g., bioretention and green roofs) within the Morgan State University (MSU) campus were collected, processed, and analyzed using this integrated framework. Results indicated that the framework yielded highly accurate predictions of plant density with a high R2 value of 95.8% and lower estimation errors of between 3.9% and 9.7%. Plant density was observed to vary between 63.63% and 75.30% in the GSIs at the MSU campus, potentially attributable to the different types of GSI, varying facility ages, and inadequate maintenance. Normalized difference vegetation index (NDVI) maps and scales of two GSIs were also generated to evaluate plant health. The NDVI and plant density results can be used to suggest where new plants can be added and to provide proper maintenance to achieve proper functions within the GSIs. This study provides a framework for evaluating plant performance within the GSIs using the collected UAV-based imagery.

Bringing together a genealogy of authors, concepts, and aesthetic case studies, this article aims to contribute to the discussion on ordinary aesthetics by focusing on the tensions that are intrinsic to walking as a fundamental embodied action in everyday urban life. These tensions concern the movement of walking itself and its relation to one’s surroundings, but it also concerns a certain complementarity between home (familiarity) and wandering. Experiencing space and thresholds that disrupt one’s relationship with home and the everyday can be understood as part of a modern “anti-home” tendency that lies at the core of several artistic and aesthetic practices. On the other hand, the study of walking and its relationship with the ordinary has also been enhanced and complexified by the mediation of images and technologies of reproduction. Approaching the paradoxes and ambiguities of everydayness from the perspective of walking allows us to better understand the ordinary as an in-between concept composed of evidence and mystery, familiarity and strangeness. Walking itself, as an ordinary element of life, is an unstable stabilisation, an unconsciousness that may become awareness, an immersive action that knows interruptions, a way of repeating paths that can also lead to detours and discoveries.

Over the past three decades, there has been a significant increase in political and media attention towards climate change. The media has been instrumental in shaping, reproducing, and influencing the political and cultural comprehension of this phenomenon. While previous research has concentrated primarily on the textual content of news articles, this study focuses on the use of images in climate communication. It is based on the belief that images can combine facts and emotions, engaging audiences and adding narrative complexity to verbal claims. With focus on climate imagery, a content analysis was conducted on 1010 images used by a Portuguese newspaper (Público) between January 2000 and May 2022 to visually cover climate change. The purpose of the analysis was to identify the visual frames used by the newspaper to frame the issue. The primary findings indicate that 35.5% of the images analyzed employ a frame that dramatizes the effects of climate change, evoking anxiety and vulnerability. However, there is evidence of a growing body of scientific literature that challenges and refutes the sensationalist and demoralizing narrative, resulting in the development of novel methods of communicating the phenomenon. Compared to the preceding period (2000–2005), the proportion of visual frames depicting potential solutions and adaptation strategies has increased substantially over the past three years (2020–2022) by 16.3%.

Not all frameworks used in machine learning and deep learning integrate with Android, which requires some prerequisites. The primary objective of this paper is to present the results of the analysis and a comparison of deep learning development frameworks, which can be adapted into fully decentralized Android apps from a cloud server. As a work methodology, we develop and/or modify the test applications that these frameworks offer us a priori in such a way that it allows an equitable comparison of the analysed characteristics of interest. These parameters are related to attributes that a user would consider, such as (1) percentage of success; (2) battery consumption; and (3) power consumption of the processor. After analysing numerical results, the proposed framework that best behaves in relation to the analysed characteristics for the development of an Android application is TensorFlow, which obtained the best score against Caffe2 and Snapdragon NPE in the percentage of correct answers, battery consumption, and device CPU power consumption. Data consumption was not considered because we focus on decentralized cloud storage applications in this study.

Konzepte im Umgang mit anderen Kulturen und Religionen wirken über konkreteRepräsentationen auf Kinder und Jugendliche ein. Dieses Zusammenspiel sollexemplarisch am missionspädagogischen Konzept gezeigt werden, das bis insletzte Jahrhundert hinein dominierte. Die immanenten hegemonialen und asymmetrischenDenkmuster dieser eurozentrischen Sicht auf die globale Welt lassensich über die konkreten Repräsentationen, z.B. Bilder, Artefakte und Handlungsaufforderungen,bis hin zu den Wirkungen nachverfolgen, die aus autobiografischenDarstellungen erhoben werden.

This paper presents a novel computational process used for determining matching coefficients for optical spectra either in real time or from a database. This simple algorithmic method is capable of outputting a set of coefficients relating to comparative matching datapoints and to a weighted similarity ratio between spectra whilst still maintaining high computational efficiency due to the minimization of floating-point calculations. The process works as effectively on signal data during real time processing or on images of spectra which may be stored in a database. A subset of the algorithm has already been used very effectively in an embedded mobile field device to determine the presence or absence of special security fluorescent emission peaks present in printing inks used in anti-counterfeiting labels. The process involves the division of test spectrum(s) signal/image into a grid of user definable blocks while applying the same grid to the test image or images. Each block is then checked to see if the signal/image passes through the block, if the signal/image passes through a block then the value of this grid block is set to 1 in a grid array. The same check is then applied to the reference signal/image(s).While it is possible to process a signal comparison without the need for data storage, useful for some embedded processes, it may be preferable to store the resultant data in simple data arrays. These arrays can then undergo simple arithmetical processing to quickly calculate a set of values representing the number of matching data points, the variation in non-matching data points and a divergence value. This check can be carried out between the test image or images and a larger number of reference images simultaneously by use of additional counters. In addition, when used with large databases of spectra this novel technique may be used to rapidly reduce a large test set to a more relevant subset which can be further analyzed using more conventional methods or by visual inspection. This grid square analysis method works as efficiently on images as it can for signal data and it is believed by the authors that the method will have applications in other image processing applications where fast and efficient comparative analysis between images is required.

Anne-Katrin Weber, Television Before TV: New Media and Exhibition Culture in Europe and the USA, 1928-1939 (Amsterdam: Amsterdam University Press, 2022), pp. 390,ISBN: 9789463727815 (hb), €106; ISBN 9789048544813 (ebook PDF Open Access), €0.00.

Review of Idurre Alonso and Maristella Casciato, The Metropolis in Latin America, 1830–1930, Los Angeles: Getty Research Institute, 2021, 324 pages (ISBN 978-1-60606-694-2). This large-format book traces the history of the metropolitan transformations of the great Latin American cities and is accompanied by an impressive corpus of historical images.

Dans mes recherches sur cette philosophie, je me suis rendu compte que les grands écrivains du cinéma et de l’image, de la philosophie, de la sociologie et de l’anthropologie, de la psychologie et de la neurologie, et les critiques apportent tous des réponses aux questions du genre. Qu’est-ce qu’un film, à quoi sert telle ou telle image, et une explication concrète de comment filmer tel ou tel motif ici et là. Ce qui rend cela important pour la poursuite de la recherche et de l’expertise, c’est la lecture des images et la capacité de comprendre l’espace créé par le magicien, où les images sont vues et intégrées dans des scénarios, et de lire ces représentations pour comprendre le magicien.

In this special issue, we explore the role of depictions and images in religious traditions from both theoretical and empirical perspectives, covering a broad spectrum of religious traditions from Asia to Europe. Our focus is on examining the range of religious attitudes towards images, which can range from indifference (aniconism) to admiration (iconism) to outright rejection and destruction (anti-iconism). Our contributors discuss the hypothesis that religious attitudes towards images often fluctuate between these three categories, and that it is not possible to strictly classify a particular religious tradition as either hostile or friendly towards images. This introduction provides an overview of the central and complex concepts that form the basis of the individual contributions, including representation, icons, media and materiality, and an/iconism.