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Automation, including machine learning technologies, are becoming increasingly crucial in agriculture to increase productivity. Machine vision is one of the most popular parts of machine learning and has been widely used where advanced automation and control have been required. The trend has shifted from classical image processing and machine learning techniques to modern artificial intelligence (AI) and deep learning (DL) methods. Based on large training datasets and pre-trained models, DL-based methods have proven to be more accurate than previous traditional techniques. Machine vision has wide applications in agriculture, including the detection of weeds and pests in crops. Variation in lighting conditions, failures to transfer learning, and object occlusion constitute key challenges in this domain. Recently, DL has gained much attention due to its advantages in object detection, classification, and feature extraction. DL algorithms can automatically extract information from large amounts of data used to model complex problems and is, therefore, suitable for detecting and classifying weeds and crops. We present a systematic review of AI-based systems to detect weeds, emphasizing recent trends in DL. Various DL methods are discussed to clarify their overall potential, usefulness, and performance. This study indicates that several limitations obstruct the widespread adoption of AI/DL in commercial applications. Recommendations for overcoming these challenges are summarized.

This paper explores the extent to which the recent turbulent history of Cyprus is reflected in an emblematic building, the Ledra Palace Hotel. The hotel is situated on Nicosia's buffer zone, the Green Line that, since 1964, has divided the island into Greek Cypriot and Turkish sectors. Since its establishment in 1949 the Ledra Palace has been the background of the country's key historical events. In this paper, the Ledra Palace is analysed as an integral part of Cyprus’ cultural heritage which contributes to the understanding and negotiation of the island's difficult past.

they have been transmitted from generation to generation, along different countries, mainly due to movements of people carrying and disseminating their civilization. Studying the contextual correlation of dances along neighboring countries, unveils the evolution of this unique intangible heritage in time, and helps in understanding potential cultural similarities. In this work we present a method for contextually motion analysis that organizes dance data semantically, to form the first digital dance ethnography. Firstly, we break dance motion sequences into some narrow temporal overlapping feature descriptors, named motion and style words, and then cluster them in a high-dimensional features space to define motifs. The distribution of those motion and style motifs creates motion and style signatures, in the content of a bag-of-motifs representation, that implies for a succinct but descriptive portrayal of motions sequences. Signatures are time-scale and temporal-order invariant, capable of exploiting the contextual correlation between dances, and distinguishing fine-grained difference between semantically similar motions. We then use quartet-based analysis to organize dance data into a categorization tree, while inferred information from dance metadata descriptions are then used to set parent-child relationships. We illustrate a number of different organization trees, and portray the evolution of dances over time. The efficiency of our method is also demonstrated in retrieving contextually similar dances from a database. each dance produces a meaning, a story with the help of music, costumes and dance moves. However, dances have no borders Folk dances often reflect the socio-cultural influences prevailing in different periods and nations 12 4

s objects and narratives. The aim of this paper is to explore the practices, experiences, and perceptions of museum professionals on the use of VR technology in museums, their perceived advantages and challenges of such technologies, and their vision for the future of technology in museums. The paper provides an in-depth analysis of interviews with museum professionals from a number of countries around the world who worked with particular VR projects in their own institutions. The ultimate aim is to offer a more critical and holistic examination and assessment of the use of VR in museums and provide suggestions for designing and developing VR projects in the future. The past few years have seen an increase in the use of virtual reality (VR) in museum environments in an attempt for museums to embrace technological innovations and adapt to the challenges of the digital era. While there are studies that examine the advantages of VR in museums and visitors&rsquo experiences with it, there are no studies examining the experiences of museum professionals who are responsible for a museum&rsquo

Abstract Contemporary discourse points to the central role that heritage plays in the process of enabling groups of various cultural or ethnic background to strengthen their feeling of belonging and sharing in society. Safeguarding heritage is also valued highly in the priorities of the European Commission. As a result, there have been several long-term initiatives involving the digitisation, annotation and cataloguing of tangible cultural heritage in museums and collections. Specifically, for built heritage, a pressing challenge is that historical monuments such as buildings, temples, churches or city fortification infrastructures are hard to document due to their historic palimpsest; spatial transformations, actions of destruction, reuse of material, or continuous urban development that covers traces and changes the formal integrity and identity of a cultural heritage site. The ability to reason about a monument’s form is crucial for efficient documentation and cataloguing. This paper presents a 3D digitisation workflow through the involvement of reality capture technologies for the annotation and structure analysis of built heritage with the use of 3D Convolutional Neural Networks (3D CNNs) for classification purposes. The presented workflow contributes a new approach to the identification of a building’s architectural components (e.g., arch, dome) and to the study of the stylistic influences (e.g., Gothic, Byzantine) of building parts. In doing so this workflow can assist in tracking a building’s history, identifying its construction period and comparing it to other buildings of the same period. This process can contribute to educational and research activities, as well as facilitate the automated classification of datasets in digital repositories for scholarly research in digital humanities.

Image annotation is the process of assigning metadata to images, allowing effective retrieval by text-based search techniques. Despite the lots of efforts in automatic multimedia analysis, automatic semantic annotation of multimedia is still inefficient due to the problems in modeling high-level semantic terms. In this paper, we examine the factors affecting the quality of annotations collected through crowdsourcing platforms. An image dataset was manually annotated utilizing: (1) a vocabulary consists of preselected set of keywords, (2) an hierarchical vocabulary and (3) free keywords. The results show that the annotation quality is affected by the image content itself and the used lexicon. As we expected while annotation using the hierarchical vocabulary is more representative, the use of free keywords leads to increased invalid annotation. Finally, it is shown that images requiring annotations that are not directly related to their content (i.e., annotation using abstract concepts) lead to accrue annotator inconsistency revealing in that way the difficulty in annotating such kind of images is not limited to automatic annotation, but it is a generic problem of annotation.

storytelling. The hypothesis that the modern immersive archaeological VR application presenting cultural heritage from a submerged site would sustain high levels of presence, immersion, and general engagement was leveraged in the investigation of the user experience with both the subjective (questionnaires) and the objective (neurophysiological recording of the brain signals using electroencephalography (EEG)) evaluation methods. Participants rated the VR experience positively in the questionnaire scales for presence, immersion, and subjective judgement. High positive rating concerned also the psychological states linked to the experience (engagement, emotions, and the state of flow), and the experience was mostly free from difficulties linked to the accustomization to the VR technology (technology adoption to the head-mounted display and controllers, VR sickness). EEG results are in line with past studies examining brain responses to virtual experiences, while new results in the beta band suggest that EEG is a viable tool for future studies of presence and immersion in VR. This paper presents a combined subjective and objective evaluation of an application mixing interactive virtual reality (VR) experience with 360°