14,571 Results Found

Background: This study investigates the efficacy of Front-of-Pack Nutrition Labels (FOPNLs) as a cost-effective tool for improving dietary choices among Greek consumers. The purpose of the study was to investigate Greek customers’ preferences a...

In the ongoing debate about front-of-package (FOP) nutrition labels, little data exist regarding nutritionally at-risk populations, although they are critical targets of prevention programs. This study aimed to compare the impact of FOP labels on the...

As a result of the large semantic gap between the low-level features and the high-level semantics, scene understanding is a challenging task for high satellite resolution images. To achieve scene understanding, we need to know the contents of the sce...

Instance-level data augmentation methods, exemplified by “copy-paste”, serve as a conventional strategy for improving the performance of small object detectors. The core idea involves leveraging background redundancy by compositing object...

Understanding flood scenes is essential for effective disaster response. Previous research has primarily focused on computer vision-based approaches for analyzing flood scenes, capitalizing on their ability to rapidly and accurately cover affected re...

As a fundamental and important task in remote sensing, remote sensing image scene understanding (RSISU) has attracted tremendous research interest in recent years. RSISU includes the following sub-tasks: remote sensing image scene classification, rem...

The incidence of overweight and obesity has generated significant concerns among European consumers and institutions. As part of a set of measures undertaken, the European Union (EU) called for one harmonized mandatory front-of-pack nutritional label...

The demand for creating automatic text summarization methods has significantly emerged as a result of the web’s explosive growth in textual data and the challenge of finding re-quired information within this massive volume of data. Multi-docume...

Visual perception is a critical task for autonomous driving. Understanding the driving environment in real time can assist a vehicle in driving safely. In this study, we proposed a multi-task learning framework for simultaneous traffic object detecti...

As a prerequisite for autonomous driving, scene understanding has attracted extensive research. With the rise of the convolutional neural network (CNN)-based deep learning technique, research on scene understanding has achieved significant progress....

Accounts of revelation and contemporary views of these are based on beliefs and historical citations. These accounts shall not be limited to the understanding and interpreting of historical and other events within writings but must present the possib...

Object detection, visual relationship detection, and image captioning, which are the three main visual tasks in scene understanding, are highly correlated and correspond to different semantic levels of scene image. However, the existing captioning me...

Wittgenstein’s philosophy has influenced the philosophy of religion quite considerably. This is hardly due to his rather few remarks on religion. Instead, Wittgenstein’s influence seems to be connected to a certain, without doubt common,...

Recent studies have shown that deep learning achieves excellent performance in reconstructing 3D scenes from multiview images or videos. However, these reconstructions do not provide the identities of objects, and object identification is necessary f...

Front-of-Package labels (FoPLs) are efficient tools for increasing consumers’ awareness of foods’ nutritional quality and encouraging healthier choices. A label’s design is likely to influence its effectiveness; however, few studies...

Alzheimer’s disease (AD) is a neurodegenerative disease that affects a large number of people across the globe. Even though AD is one of the most commonly seen brain disorders, it is difficult to detect and it requires a categorical representat...

Over the past decades, both industry and academy have made enormous advancements in the field of intelligent vehicles, and a considerable number of prototypes are now driving our roads, railways, air and sea autonomously. However, there is still a lo...

The paper is a survey of the main technological aspects of advanced visual-based surveillance systems. A brief historical view of such systems from the origins to nowadays is given together with a short description of the main research projects in It...

Detecting salient objects in complicated scenarios is a challenging problem. Except for semantic features from the RGB image, spatial information from the depth image also provides sufficient cues about the object. Therefore, it is crucial to rationa...

Pose estimation of free-form objects is a crucial task towards flexible and reliable highly complex autonomous systems. Recently, methods based on range and RGB-D data have shown promising results with relatively high recognition rates and fast runni...

Recently, 6D pose estimation methods have shown robust performance on highly cluttered scenes and different illumination conditions. However, occlusions are still challenging, with recognition rates decreasing to less than 10% for half-visible object...

The ability of artificial intelligence to drive toward an intended destination is a key component of an autonomous vehicle. Different paradigms are now being employed to address artificial intelligence advancement. On the one hand, modular pipelines...

With the ubiquitous use of mobile imaging devices, the collection of perishable disaster-scene data has become unprecedentedly easy. However, computing methods are unable to understand these images with significant complexity and uncertainties. In th...

Law Enforcement Agencies (LEAs) typically analyse vast collections of media files, extracting visual information that helps them to advance investigations. While recent advancements in deep learning-based computer vision algorithms have revolutionise...

This paper introduces a hierarchical object-centric descriptor framework called TOSD (Triplet Object-Centric Semantic Descriptor). The goal of this method is to overcome the limitations of existing pixel-based and global feature embedding approaches....

Learning from Demonstration (LfD) enables robots to acquire manipulation skills by observing human actions. However, existing methods often face challenges such as high computational cost, limited generalizability, and a loss of key interaction detai...

Autonomous driving (AD) systems remain vulnerable to rare, ambiguous, and out-of-label (OOL) hazards that are insufficiently represented in conventional training datasets. This work investigates perception robustness under such conditions by using th...

Image understanding plays a pivotal role in various computer vision tasks, such as extraction of essential features from images, object detection, and segmentation. At a higher level of granularity, both semantic and instance segmentation are necessa...

This article describes a novel fusion of a generative formal model for three-dimensional (3D) shapes with deep learning (DL) methods to understand the geometric structure of 3D objects and the relationships between their components, given a collectio...

Catering to Halal in the industry requires the explicit adoption of Halal Logistics (HL) to avoid the risk of cross-contamination and ensure that Halal products are safe, hygienic, nutritious, pure, unadulterated, and consistent with their labelling....

In outcome-based academic programs, Program Education Objects (PEOs) are the key pillars on which program components are built. They are articulated linguistically as broad statements of graduates’ professional and career accomplishments within a few...

According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) syste...

According to literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) systems, where...

This article makes the case for more objectivity in Machine Learning (ML) research. Any research work that claims to hold benefits has to be scrutinized based on many parameters, such as the methodology employed, ethical considerations and its theore...

Underwater image enhancement is often perceived as a disadvantageous process to object detection. We propose a novel analysis of the interactions between enhancement and detection, elaborating on the potential of enhancement to improve detection. In...

Video surveillance systems process high volumes of image data. To enable long-term retention of recorded images and because of the data transfer limitations in geographically distributed systems, lossy compression is commonly applied to images prior...

Accurate depth perception is vital for autonomous driving and roadside monitoring. Traditional stereo vision methods are cost-effective but often fail under challenging conditions such as low texture, reflections, or complex lighting. This work prese...

Camouflaged object detection (COD) represents one of the most challenging tasks in computer vision, requiring sophisticated approaches to accurately extract objects that seamlessly blend within visually similar backgrounds. While contemporary techniq...

Poly(lactic acid) (PLA) is the most widely used feedstock in material extrusion (MEX) 3D printing. In this study, PLA was combined with 0–40 wt.% of poly(butylene adipate-co-terephtalate) (PBAT) to improve its ductility. The resulting blends we...

The integration of thermal imaging data with multimodal large language models (MLLMs) offers promising advancements for enhancing the safety and functionality of autonomous driving systems (ADS) and intelligent transportation systems (ITS). This stud...

Dietary practices are a key behavioral factor in chronic disease prevention; one strategy for improving such practices population-wise involves front-of-package labels (FoPL). This online randomized study, conducted in a quota-based sample of 1159 Po...

As one of the primary means of Earth observation, high-spatial-resolution remote sensing images can describe the geometry, texture and structure of objects in detail. It has become a research hotspot to recognize the semantic information of objects,...

Graphs are prevalent in the reports of the Intergovernmental Panel on Climate Change (IPCC), often depicting key points and major results. However, the popularity of graphs in the IPCC reports contrasts with a neglect of empirical tests of their unde...

This paper presents best practices on how to design reminder objects. Reminder objects are digitally augmented everyday objects that break down and communicate complex information via sensory input and output. In the first section of this paper, we i...

What makes unmanned aerial vehicles (UAVs) intelligent is their capability of sensing and understanding new unknown environments. Some studies utilize computer vision algorithms like Visual Simultaneous Localization and Mapping (VSLAM) and Visual Odo...

Accurate object registration is crucial for precise localization and environment sensing in autonomous driving systems. While real-time sensors such as cameras and radar capture the local environment, high-definition (HD) maps provide a global refere...

Along with studies on artificial intelligence technology, research is also being carried out actively in the field of natural language processing to understand and process people’s language, in other words, natural language. For computers to le...

Object detection in optical remote sensing images is still a challenging task because of the complexity of the images. The diversity and complexity of geospatial object appearance and the insufficient understanding of geospatial object spatial struct...

Policy understanding toward energy conservation is fundamental for voluntary energy-saving activities in the industrial sector. To increase policy understanding, government communication has been regarded as a means of helping enterprises to recogniz...

The source of characters is hieroglyph. Hieroglyph is the imitation and reference of the phenomena and objects in the natural world. The objects and phenomena in the natural world are the original image. Or rather its own figurative meta-hieroglyphic...