Do DMOs Promote the Right Aspects of the Destination? A Study of Instagram Photography with a Visual Classifier

As global travel emerges from the pandemic, pent up interest in travel will lead to consumers making their choice between global destinations. Instagram is a key source of destination inspiration. DMO marketing success on this channel relies on projecting a destination image that resonates with this target group. However, usual text-based marketing intelligence on this channel does not work as content is consumed first and foremost as a visual projection. The author has built a deep learning based visual classifier for destination image measurement from photos. In this paper, we compare projected and perceived destination images in Instagram photography for four of the most Instagrammed destinations worldwide. We find that whereas the projected destination image aligns well to the perceived image, there are specific aspects of the destinations that are of more interest to Instagrammers than reflected in the current destination marketing.

Experimental Validation of Non-Marker Simple Image Displacement Measurements for Railway Bridges

Simple bridge displacement measurement using a video camera is effective in realizing the efficient management of numerous railway structures via condition-based maintenance. Although non-marker image measurement is significantly influenced by the measuring environment, its practical applicability considering the displacement measurement accuracy of non-marker images and the influence of various environments is not completely understood. In this study, the accuracy of non-marker image displacement measurement and the influence of illuminance are confirmed using a model bridge, and the accuracy and applicable range are discussed. Moreover, field tests on two bridges—a steel and a concrete bridge—on low-speed and high-speed railways confirm the accuracy and practical application of non-marker image measurement in a real environment. The displacement was observed to be measured with an accuracy of ~1/30 pixel (error of ~0.4 mm at 20 m position) in the daytime with sufficient brightness. Moreover, the settings for subset positions and post-processing methods to ensure accuracy in non-marker image measurement on concrete bridges with low surface contrast are discussed.

IMAGE AS AN IMPORTANT TOOL IN THE WORK OF MANAGERS OF EDUCATIONAL INSTITUTIONS

The aim of the paper is to present the results of a survey focused on the image of an educational institution - a public university in the Czech Republic, which provides study programs for future teachers of vocational subjects at secondary schools. The image of an educational institution is an integral part of the management of educational institutions and at the same time, it should be a part of its regular self-evaluation. An image consists of objective and subjective, correct and incorrect ideas, attitudes and experiences of an individual or a certain group of people about a certain object or subject. Image affects opinions and behaviour and significantly influences them [1]. Each educational institution creates a certain image, through which it can be perceived not only by its surroundings or social partners, but mainly by current and future students. Particularly, the students were the respondents to this survey. The method of semantic differential (polarity profile), which is one of the most frequently used methods for image measurement, was used for data collection.