Abstract
In this study, we evaluated the use of small pre-trained 3D Convolutional Neural Networks (CNN) on land use and land cover (LULC) slide-window-based classification. We pre-trained the small models in a dataset with origin in the Eurosat dataset and evaluated the benefits of the transfer-learning plus fine-tuning for four different regions using Sentinel-2 L1C imagery (bands of 10 and 20m of spatial resolution), comparing the results to pre-trained models and trained from scratch. The models achieved an F1 Score of between 0.69-0.80 without significative change when pre-training the model. However, for small datasets, pre-training the model improved the classification by up to 3%.

Abstract
The grapevine variety identification is important in the wine's production chain since it is related to its quality, authenticity and singularity. In this study, we addressed the data augmentation approach to identify grape varieties with images acquired in-field. We tested the static transformations, RandAugment, and Cutmix methods. Our results showed that the best result was achieved by the Static method generating 5 images per sample (F1 = 0.89), however without a significative difference if compared with RandAugment generating 2 images. The worst performance was achieved by CutMix (F1 = 0.86).

Abstract
Empathy has become a central part of design and is loudly manifested in several frameworks such as universal design, inclusive design or human-centred design. This paper presents five independent Extended Reality (XR) scenarios that put potential users in the shoes of people with special needs such as vision impairments, autism spectrum disorder, mobility impairments, pregnancy state and some problems of the elderly. All exercises occur in a supermarket environment and the application is prepared for Oculus Quest 2 platform and is supported in some cases by tangible equipment (geriatric suit, pregnancy belly simulator, wheelchair). The proposed simulations were validated by experts who evaluated the quality of the proposed tasks and the possibility of simulating selected limitations or issues in XR. Ongoing development and testing of the XR application will provide further in-depth views on its usefulness, acceptance and impact in increasing empathy towards the challenges faced by the personas portrayed.

Abstract
The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

Abstract
Artificial Intelligence (AI) has evolved rapidly since its inception in the 1950s, from simple rule-based systems to today's advanced deep learning models. AI has impacted society in many ways, ranging from revolutionizing the way we live, work, and interact with technology, to creating new job opportunities, improving decision-making and automating tasks, and solving complex problems in fields like healthcare, finance, and transportation. However, it has also raised concerns about job displacement, privacy and security, and ethical considerations. The evolution of AI is ongoing, and it is expected to continue to shape and transform society in new and profound ways. The impact of AI in education has also been substantial, offering new and innovative ways to personalize learning, enhance educational resources, and improve educational outcomes. In this chapter we will cover the most important aspects related with the teaching-learning process, from a physiological perspective to the different strategies. © 2023, IGI Global. All rights reserved.

Abstract
Background: Virtual reality (VR) has the potential to be a powerful tool in promoting empathy towards inclusion, particularly for individuals with impairments such as mobility difficulties, vision deficits, or autism but also about pregnancy, which can create temporary difficulties. By immersing users in simulated environments that replicate the experiences of those with different abilities, VR can create a sense of understanding and empathy for those who face challenges in their daily lives. For example, VR experiences can simulate the experience of navigating space as someone with a mobility impairment, providing a new perspective and appreciation for the difficulties that others face. Similarly, VR experiences can simulate the experience of vision impairment, pregnancy, or autism, providing a window into the challenges faced by those with these conditions and fostering empathy and understanding. Material and Methods: During the development of this study, field experts were consulted to ensure the robustness of the methods employed. Then, questionnaires were specifically developed to explore disabilities and challenges related to inclusion and were administered to a large population. Additionally, guided interviews were conducted with individuals who possess specific impairments to gather first-hand insights. Results: The results obtained from the questionnaires and interviews provide a comprehensive overview of the inclusion challenges that necessitate attention and resolution. By drawing on the expertise of both experts and individuals with lived experiences, a holistic landscape of inclusion challenges has been established. Conclusions: The VR emerges as a powerful tool for promoting inclusion and fostering understanding among individuals. Its capacity to create immersive experiences that facilitate empathy has the potential to reshape society into a more compassionate and empathetic one. By leveraging the unique capabilities of VR, we can bridge the gap between different perspectives, fostering greater understanding, acceptance, and inclusivity.