Remote sensing image change captioning (RSICC) fuses computer vision and natural language processing to translate visual differences between bi-temporal remote sensing images into interpretable text, with applications in environmental monitoring, urb...
Remote sensing image change captioning (RSICC) aims to automatically generate sentences describing the difference in content in remote sensing bitemporal images. Recent works extract the changes between bitemporal features and employ a hierarchical a...
Remote sensing image change captioning (RSICC) has received considerable research interest due to its ability of automatically providing meaningful sentences describing the changes in remote sensing (RS) images. Existing RSICC methods mainly utilize...
Remote Sensing Image Change Captioning (RSICC) has emerged as a cross-disciplinary technology that automatically generates sentences describing the changes in bi-temporal remote sensing images. While demonstrating significant potential for urban plan...
Remote sensing image change captioning (RSICC) aims to describe changes between bi-temporal remote sensing (RS) images in natural language. The existing methods, typically based on traditional encoder–decoder architectures or multi-task collabo...
Remote Sensing Image Change Captioning (RSICC) aims to generate natural language descriptions of changes in bi-temporal remote sensing images, providing more semantically interpretable results than conventional pixel-level change detection methods. H...
Understanding complex change scenes is a crucial challenge in remote sensing field. Remote sensing image change captioning (RSICC) task has emerged as a promising approach to translate appeared changes between bi-temporal remote sensing images into t...
Describing land cover changes from multi-temporal remote sensing imagery requires capturing both visual transformations and their semantic meaning in natural language. Existing methods often struggle to balance visual accuracy with descriptive cohere...
This study proposes a framework for describing a scene change using natural language text based on indoor scene observations conducted before and after a scene change. The recognition of scene changes plays an essential role in a variety of real-worl...
Image captioning is a problem of viewing images and describing images in language. This is an important problem that can be solved by understanding the image, and combining two fields of image processing and natural language processing into one. The...
Image captioning is a very important task, which is on the edge between natural language processing (NLP) and computer vision (CV). The current quality of the captioning models allows them to be used for practical tasks, but they require both large c...
Recent video captioning models aim at describing all events in a long video. However, their event descriptions do not fully exploit the contextual information included in a video because they lack the ability to remember information changes over time...
In this paper, we propose a novel method for producing image captions through the utilization of Generative Adversarial Networks (GANs) and Vision Transformers (ViTs) using our proposed Image Captioning Utilizing Transformer and GAN (ICTGAN) model. H...
In order to understand and fully comprehend a subtitle, two parameters within the linguistic code of audiovisual texts are key in the processing of the subtitle itself, namely, vocabulary and syntax. Through a descriptive and experimental study, the...
The accurate interpretation of land cover changes in multi-temporal satellite imagery is critical for Earth observation. However, existing methods typically yield static outputs—such as binary masks or fixed captions—lacking interactivity...
(1) Flatfoot is a common malformation in both children and adults, in which a proper arch fails to develop. This study aimed to see how over-the-counter running shoes improved the gait patterns of flatfoot patients. (2) Methods: Three healthy flatfoo...
Stakeholders from public, private, and third sectors need to adapt to a changing climate. Communications about climate may be challenging, especially for audiences with limited climate expertise. Here, we study how such audience members perceive visu...
High-quality Earth Observation (EO) imagery is essential for accurate analysis and informed decision making across sectors. However, data scarcity caused by atmospheric conditions, seasonal variations, and limited geographical coverage hinders the ef...
Heart rate is an essential vital sign to evaluate human health. Remote heart monitoring using cheaply available devices has become a necessity in the twenty-first century to prevent any unfortunate situation caused by the hectic pace of life. In this...
27 October 2014
Research informs action, but the challenge is its translation into practice. The 2012–2017 National Institute of Environmental Health Sciences Strategic Plan emphasizes partnership with community stakeholders to capture critical missing information...
Water distribution infrastructure (WDI) is well-established and significantly improves living quality. Nonetheless, aging WDI has posed an awkward worldwide problem, wasting natural resources and leading to direct and indirect economic losses. The to...
We report the synthesis of poly(styrene-block-lactic acid) (PS-b-PLA) copolymers with triazole rings as a junction between blocks. These materials were prepared via a ‘click’ strategy which involved the reaction between azide-terminated p...
Background. Nurses’ perceptions of health are essential to decision making and communicating with clients. However, little is known about their own perceptions of this phenomenon. This study focuses on health-related beliefs among young nurses...
This editorial introduces the Special Issue, entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries”, of Electronics. Topics covered in this issue include four main parts: (I) environmental informat...