Recently, hyperspectral image (HSI) classification has attracted increasing attention in the remote sensing field. Plenty of CNN-based methods with diverse attention mechanisms (AMs) have been proposed for HSI classification due to AMs being able to...
Semantic segmentation of street view images is an important step in scene understanding for autonomous vehicle systems. Recent works have made significant progress in pixel-level labeling using Fully Convolutional Network (FCN) framework and local mu...
In order to make the classification and regression of single-stage detectors more accurate, an object detection algorithm named Global Context You-Only-Look-Once v3 (GC-YOLOv3) is proposed based on the You-Only-Look-Once (YOLO) in this paper. Firstly...
Head detection is a fundamental task, and it plays an important role in many head-related problems. The difficulty in creating the local and global context in the face of significant lighting, orientation, and occlusion uncertainty, among other facto...
Recently, many researchers have been dedicated to using convolutional neural networks (CNNs) to extract global-context features (GCFs) for remote-sensing scene classification. Commonly, accurate classification of scenes requires knowledge about both...
Synthetic aperture radar (SAR) is an advanced microwave sensor, which has been widely used in ocean surveillance, and its operation is not affected by light and weather. SAR ship instance segmentation can provide not only the box-level ship location...
Precise segmentation of flotation froths is a critical bottleneck to achieving intelligent perception and optimal control of process operations. Traditional convolutional neural networks (CNNs) are inherently limited by local receptive fields, making...
Fine-grained food-image recognition is difficult because visually similar dishes can differ only in small ingredient or texture cues, while images of the same dish vary in plating, viewpoint, illumination, and background. We propose Dynamic Global Co...
With the rapid development of deep neural networks, salient object detection has achieved great success in natural images. However, detecting salient objects from optical remote sensing images still remains a challenging task due to the diversity of...
Ancient paintings, as a vital component of cultural heritage, encapsulate a profound depth of cultural significance. Over time, they often suffer from different degradation conditions, leading to damage. Existing ancient painting inpainting methods s...
The rapid development of Earth observation technology has promoted the continuous accumulation of images in the field of remote sensing. However, a large number of remote sensing images still lack manual annotations of objects, which makes the strong...
Animal behavior recognition is an important research area that provides insights into areas such as neural functions, gene mutations, and drug efficacy, among others. The manual coding of behaviors based on video recordings is labor-intensive and pro...
Accurate extraction of mountaintop areas from grid digital elevation models (DEMs) is essential for terrain analysis, geomorphological research, hydrological modeling, natural disaster monitoring, and emergency communication site selection. However,...
Accurate identification of mango varieties holds substantial significance for the elevation of product added value and the facilitation of market differentiation through quality-based pricing. Near-infrared (NIR) spectral analysis offers a rapid, non...
Cervical cancer is a worldwide public health problem with a high rate of illness and mortality among women. In this study, we proposed a novel framework based on Faster RCNN-FPN architecture for the detection of abnormal cervical cells in cytology im...
Change detection in high-resolution optical remote sensing images is essential for dynamic surface monitoring and land resource management. However, existing methods still face challenges in representing multiscale change information, accurately loca...
Building extraction from remote sensing imagery plays a pivotal role in applications such as smart cities, urban planning, and disaster assessment. Although deep learning has significantly advanced this task, existing methods still struggle to strike...
Fully convolutional structures provide feature maps acquiring local contexts of an image by only stacking numerous convolutional layers. These structures are known to be effective in modern state-of-the-art object detectors such as Faster R-CNN and S...
Glaucoma is a chronic progressive optic neuropathy causing irreversible blindness globally, underscoring the need for reliable diagnostic tools. While visual field (VF) testing remains the clinical standard, it has significant limitations, including...
Although there have been recent advances in Siamese-network-based visual tracking methods where they show high performance metrics on numerous large-scale visual tracking benchmarks, persistent challenges regarding the distractor objects with similar...
We introduced this Special Issue entitled “Challenges and Prospects of Sustainability in the Context of Global Health”, published by MDPI, about two years ago with the following excerpt: [...]
Sustainable water use is becoming a key problem in the present time, since global warming is having a strong impact on usable water resources. This study aims to provide a systematic bibliometric analysis on water sustainability in the context of glo...
22 January 2017
This paper reviews information from the existing literature and the EU GMOS (Global Mercury Observation System) project to assess the current scientific knowledge on global mercury releases into the atmosphere, on global atmospheric transport and dep...
The article presents a synthetic analysis of the most pressing challenges associated with food security in the context of changes induced by global development and the generated problems. The study demonstrated that a more effective model of food pro...
The natural sciences are receiving increasing attention in the Global South. This timely development may help mitigate global change and quicken an envisioned food system transformation. Yet in order to resolve complex issues such as agrochemical pol...
Wetland birds are undergoing severe population declines globally, primarily attributed to extensive wetland loss and degradation. The attributes of the landscape surrounding a focal locality, referred to as ‘landscape context’, have been...
28 August 2022
The COVID-19 pandemic caused by SARS-CoV-2 remains a significant issue for global health, the economy, and society. When SARS-CoV-2 began to spread, the most recent serious infectious disease of this century around the world, with its high morbidity...
The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart citie...
Geocoding is an essential procedure in geographical information retrieval to associate place names with coordinates. Due to the inherent ambiguity of place names in natural language and the scarcity of place names in textual data, it is widely recogn...
6D object pose estimation from RGB-D data is a core problem in robotic perception. Representative approaches such as DenseFusion fuse per-pixel RGB and depth features, yet they still face challenges under heavy occlusion and in cluttered backgrounds....
As the core component of video analysis, Temporal Action Localization (TAL) has experienced remarkable success. However, some issues are not well addressed. First, most of the existing methods process the local context individually, without explicitl...
The primary objective of this research is to identify, analyse, and compare the development of risk management approaches adopted by Slovak industrial enterprises in two distinct economic periods: during a phase of economic growth (2019) and during a...
We have been observing large fluctuations and price increases in electricity markets in recent years. The COVID-19 pandemic, rising energy costs, political instability and increasing demand for electricity have been the factors intensifying the probl...
Malaria is one of the most cited vector-borne infectious diseases by climate change expert panels. Malaria vectors often need water sheets or wetlands to complete the disease life cycle. The current context of population mobility and global change re...
18 June 2020
Nowadays, cyberbullying has become a problem of social harassment in numerous educational centres worldwide. New communication technologies have provided the perfect support for the development of this type of harassment in peer relationships, in add...
The transnational ex-gay movement is an important context affecting lesbians and sexual minority women around the world. In 2015, the UN Human Rights Commissioner called for all nations to ban conversion therapies. This research investigates a neglec...
The application of deep convolutional neural networks (CNNs) has gained popularity in the field of industrial process fault diagnosis. However, conventional CNNs primarily extract local features through convolution operations and have limited recepti...
This paper aims at enhancing the previously formulated culture-theoretical explanation of risk-related perception and action with ecological and institutional connectedness. This is needed for global comparison of adaptation cultures as well as trans...
The widespread adoption of small unmanned aerial vehicles poses increasing challenges to public safety. Compared with visible-light sensors, infrared imaging offers excellent nighttime observation capabilities and strong robustness against interferen...
To address the issue of insufficient extraction of target features and the resulting impact on detection performance in long-range infrared aircraft target detection caused by small imaging area and weak radiation intensity starting from the idea of...
When “hijacked” by compulsive behaviors that affect the reward and stress centers of the brain, functional changes in the dopamine circuitry occur as the consequence of pathological brain adaptation. As a brain correlate of mental health,...
Cutaneous leishmaniasis (CL) is a vector-borne infection caused by protozoan parasites belonging to the genus Leishmania. CL is an emerging global health concern due to increasing migration, travel, and climate change. Traditionally, it was confined...
Printed circuit board (PCB) surface defect detection is an essential part of the PCB manufacturing process. Currently, advanced CCD or CMOS sensors can capture high-resolution PCB images. However, the existing computer vision approaches for PCB surfa...
This article describes the challenges and possibilities of implementing social justice language education in a difficult context in the Global South. Six Argentinian English language university teachers and tutors developed and implemented a social j...
This study examines the renewed interest in Industrialised Building (IB) adoption in Australia amid the housing crisis, addressing the gap between potential and implementation. Drawing on a systematic review of 171 peer-reviewed articles (1998–...
Since the 1980s, Mexico has undergone profound economic and political transformations grounded in neoliberalism, reflected in the opening of the agri-food sector. As a result, imports of powdered milk increased, consolidating a corporate agri-food re...
This article investigates how the “constructivist turn” in public policy and international political economy informs the interaction of global ideas and local practice in water governance. We use the implementation of ideas associated wit...
Today, international tourism is one of the most affected sectors of the economy due to the global COVID-19 pandemic. The main purpose of this article is to analyze current trends and identify prospects for the international tourism development in the...
Placental-derived pregnancy complications encompass a range of disorders that hinder optimal fetal development, significantly impacting maternal and neonatal health outcomes. Key conditions include placental insufficiency, preeclampsia, fetal growth...
Hospital billing event logs combine shared administrative routines with context-specific behavior, making a single global process model difficult to interpret. This study proposes a configurable process mining framework that complements a hospital-wi...
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