Over the last three decades, the increasing development of smart water meter trials and the rise of demand management has fostered the collection of water demand data at increasingly higher spatial and temporal resolutions. Counting these new dataset...
Land carbon fluxes play a critical role in ecosystems, and acquiring a comprehensive global database of carbon fluxes is essential for understanding the Earth’s carbon cycle. The primary methods of obtaining the spatial distribution of land car...
Mapping cropland areas is of great interest in diverse fields, from crop monitoring to climate change and food security. Recognizing the value of a reliable and harmonized crop mask that entirely covers the African continent, the objectives of this s...
Land cover information plays a critical role in supporting sustainable development and informed decision-making. Recent advancements in satellite data accessibility, computing power, and satellite technologies have boosted large-extent high-resolutio...
Obesity is a complex chronic, relapsing, progressive disease. Association studies have linked microbiome alterations with obesity and overweight. However, the results are not always consistent. An integrated analysis of 4282 fecal samples (2236 contr...
The reinforcement and renovation of existing buildings constitute an important component of the future development of the civil engineering industry. Such projects typically require the original construction drawings of the building. However, for old...
Many regions worldwide are exposed to multiple omnipresent hazards occurring in complex interactions. However, multi-hazard assessments are not yet fully integrated into current planning tools, particularly when referring to transboundary areas. This...
Building energy regulations are essential for reducing energy consumption in the European Union (EU) and achieving climate neutrality goals. This data article supplements the “Overview of EU Building Envelope Energy Requirement for Climate Neut...
This work addresses the lack of focus on verification and comparison of existing fatigue damage accumulation and life prediction models on the basis of large and well-documented experiment datasets. Sixty-four constant amplitude, 54 two-level block l...
Background/Objectives: Initial data analysis (IDA) is essential for valid and reproducible statistical analyses, but existing IDA frameworks were primarily developed for single-study datasets. Cancer registries (CRs) are extensive data systems charac...
Sentiment analysis in the Turkish language has gained increasing attention due to the growing availability of Turkish textual data across various domains. However, existing datasets often suffer from limitations such as insufficient size, lack of div...
Bedded or lying-people pressure-map datasets can be used to identify patients’ in-bed postures and can be very useful in numerous healthcare applications. However, the construction of these datasets is not always easy, and many researchers ofte...
This study questions why existing local shape descriptors have high dimensionalities (up to hundreds) despite simplicity of local shapes. We derived an answer from a historical context and provided an alternative solution by proposing a new compact d...
Building-change detection underpins many important applications, especially in the military and crisis-management domains. Recent methods used for change detection have shifted towards deep learning, which depends on the quality of its training data....
Advances in deep learning techniques for remote sensing as well as the increased availability of high-resolution data enable the extraction of more detailed information from aerial images. One promising task is the semantic segmentation of roof segme...
Machine Reading Comprehension (MRC) is a challenging Natural Language Processing (NLP) research field with wide real-world applications. The great progress of this field in recent years is mainly due to the emergence of large-scale datasets and deep...
With the rapid development of the unmanned aerial vehicle (UAV) industry and applications, the integration of UAVs into daily life has increased significantly. However, this growing presence raises security concerns, leading to the emergence of anti-...
Hi-C is a widely used technique to study the 3D organization of the genome. Due to its high sequencing cost, most of the generated datasets are of a coarse resolution, which makes it impractical to study finer chromatin features such as Topologically...
Brain tumors can have fatal consequences, affecting many body functions. For this reason, it is essential to detect brain tumor types accurately and at an early stage to start the appropriate treatment process. Although convolutional neural networks...
The task of coreference resolution concerns the clustering of words and phrases referring to the same entity in text, either in the same document or across multiple documents. The task is challenging, as it concerns elements of named entity recogniti...
UML (Unified Modeling Language) diagrams are graphical representations used in software engineering which play a vital role in the design and development of software systems and various engineering processes. Large, good-quality datasets containing U...
In handwriting recognition research, a public image dataset is necessary to evaluate algorithm correctness and runtime performance. Unfortunately, in existing Thai language script image datasets, there is a lack of variety of standard handwriting typ...
Automatic facial expression recognition is essential for many potential applications. Thus, having a clear overview on existing datasets that have been investigated within the framework of face expression recognition is of paramount importance in des...
Nowadays, HSI classification can reach a high classification accuracy when given sufficient labeled samples as training set. However, the performances of existing methods decrease sharply when trained on few labeled samples. Existing methods in few-s...
Pedestrian gender classification is one of the key assignments of pedestrian study, and it finds practical applications in content-based image retrieval, population statistics, human–computer interaction, health care, multimedia retrieval systems, de...
Climate change poses a global threat, affecting both biodiversity and human populations. To implement efficient mitigating strategies, the consistency and accuracy of our monitoring of greenhouse gases at the local level must be improved. We can achi...
Heart attack and other heart-related diseases are among the main causes of fatalities in the world. These diseases and some other severe problems like kidney failure and paralysis are mainly caused by hypertension. Since bioactive peptides extracted...
Automated vehicles, predicted to be fully electric in future, are expected to reduce road fatalities and road traffic emissions. The lane departure warning system, an important feature of automated vehicles, utilize lane detection and tracking algori...
A context-aware recommender system can make recommendations to users by considering contextual information such as time and place, not only the scores assigned to items by users. However, as a user preferences matrix is expanded in a multidimensional...
This paper consists of two parts: an overview of existing open datasets of electricity consumption and a description of the Moroccan Buildings’ Electricity Consumption Dataset, a first of its kind, coined as MORED. The new dataset comprises ele...
Digital Building Logbooks (DBLs) are the EU repositories for all building-related data. Logbook implementation conveys challenges, but it must be recognised that relevant things already exist. This article bridges the gap at the data discovery level...
Existing public domain multi-modal datasets for human action recognition only include actions of interest that have already been segmented from action streams. These datasets cannot be used to study a more realistic action recognition scenario where...
Over the last decade, a driver’s distraction has gained popularity due to its increased significance and high impact on road accidents. Various factors, such as mood disorder, anxiety, nervousness, illness, loud music, and driver’s head r...
In recent times, we have seen a massive rise in vision-based applications, such as video anomaly detection, motion detection, object tracking, people counting, etc. Most of these tasks are well defined, with a clear idea of the goal, along with prope...
Due to the complexity of real optical flow capture, the existing research still has not performed real optical flow capture of infrared (IR) images with the production of an optical flow based on IR images, which makes the research and application of...
Medical imaging tasks are very challenging due to the lack of publicly available labeled datasets. Hence, it is difficult to achieve high performance with existing deep learning models as they require a massive labeled dataset to be trained effective...
Nowdays, DNNs (Deep Neural Networks) are widely used in the field of DDoS attack detection. However, designing a good DNN architecture relies on the designer’s experience and requires considerable work. In this paper, a GA (genetic algorithm) i...
Benchmark open-source Wi-Fi fingerprinting datasets for indoor positioning studies are still hard to find in the current literature and existing public repositories. This is unlike other research fields, such as the image processing field, where benc...
Insights and analysis are only as good as the available data. Data cleaning is one of the most important steps to create quality data decision making. Machine learning (ML) helps deal with data quickly, and to create error-free or limited-error datas...
Network intrusion detection models are vital techniques for ensuring cybersecurity. However, existing models face several challenges, such as insufficient feature extraction capabilities, dataset imbalance, and suboptimal detection accuracy. In this...
The development of computer vision-based deep learning models for accurate two-dimensional (2D) image classification has enabled us to surpass existing machine learning-based classifiers and human classification capabilities. Recently, steady efforts...
Global tree cover percentage is an important parameter used to understand the global environment. However, the available global percent tree cover products are few, and efforts to validate these maps have been limited. Therefore, producing a new broa...
Today, the field of biomedical engineering spans numerous areas of scientific research that grapple with the challenges of intelligent analysis of small datasets. Analyzing such datasets with existing artificial intelligence tools is a complex task,...
Drought events exacerbated by global climate change occur frequently in China. Currently, high-spatiotemporal-resolution gridded meteorological drought index datasets are generally available for single time scales (e.g., 30, 60, 90, and 150 days) and...
Facial expression recognition (FER) plays a crucial role in various applications, including human–computer interaction and affective computing. However, the joint training of an FER network with multiple datasets is a promising strategy to enha...
Ransomware remains one of the most significant cybersecurity threats. Techniques used by attackers have evolved to bypass traditional detection methods. Many existing detection systems rely on outdated datasets or complex behavioral analyses, which a...
Accidents due to defective railway lines and derailments are common disasters that are observed frequently in Southeast Asian countries. It is imperative to run proper diagnosis over the detection of such faults to prevent such accidents. However, ma...
One of the challenges in the field of remote sensing is how to automatically identify and classify high-resolution remote sensing images. A number of approaches have been proposed. Among them, the methods based on low-level visual features and middle...
Infrared small target detection technology is widely used in infrared search and tracking, infrared precision guidance, low and slow small aircraft detection, and other projects. Its detection ability is very important in terms of finding unknown tar...
Recently, due to the rapid development and remarkable result of deep learning (DL) and machine learning (ML) approaches in various domains for several long-standing artificial intelligence (AI) tasks, there has an extreme interest in applying toward...
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