This research evaluates the regionalization of tourism in Hungary, revealing the breakdown of the national gross domestic product (GDP) of tourism. It also explores the density, spatial variations, and features of these indicators. A multimodal approach is used to evaluate the competitiveness of Hungarian counties, and the distribution of these tourism regions is analyzed using the tourism penetration index. Furthermore, regional GDP is calculated for the whole territory of Hungary. The study identifies significant regional disparities in tourism competitiveness, highlighting Budapest-Central Danube as the most competitive region and Lake Balaton as underperforming despite its potential. The research contributes by providing a detailed regional GDP analysis and emphasizing the need for targeted policy interventions to enhance tourism development across all regions.

Machine analysis of detection of the face is an active research topic in Human-Computer Interaction today. Most of the existing studies show that discovering the portion and scale of the face region is difficult due to significant illumination variation, noise and appearance variation in unconstrained scenarios. To overcome these problems, we present a method based on Extended Semi-Local Binary Patterns. For each frame, an aggregation of the pixel values over a neighborhood is considered and a local binary pattern is obtained. From these a binary code is obtained for each pixel and then histogram features is computed. Adaboost algorithm is used to learn and classify these discriminative features with the help of exemplar face and non-face signature of the images for detecting the location of face region in the frame. This Extended Semi Local Binary Pattern is sturdy to variations in illumination and noisy images. The developed methods are deployed on the real time YouTube video face databases and found to exhibit significant performance improvement owing to the novel features when compared to the existing techniques.

This paper carries out an analysis and reflection on how technoscience reaches Geography through Geographic Information Technologies, how it impacts the production of geographic knowledge and how it derives in the possibility of digital experimentation in the discipline in an environment called geo-digital reality. It is shown that advances in GIT have allowed overcoming old limitations, enriching more and more the observations made by Geography, and it is also highlighted the promising future of digital experimentation in Geography through all the possibilities offered by current technological developments.