Large Language Models (LLMs) represent a major step in AI development and are increasingly used in daily applications. However, they are prone to hallucinations, generating claims that contradict established facts, deviating from prompts, and produci...
A tropical cyclone dataset is an important data source for tropical cyclone disaster research, and the evaluation of its applicability is a necessary prerequisite. The Global Synthetic Tropical Cyclone Hazard (GSTCH) dataset is a dataset of global tr...
With the rapid development of Multimodal Large Language Models (MLLMs) in education, their applications have mainly focused on content generation tasks such as text writing and courseware production. However, automated assessment of non-exam learning...
This article presents a dataset and experimental evaluation of a parallelized variant of Junker’s QuickXPlain algorithm, designed to efficiently compute minimal conflict sets in constraint-based diagnosis tasks. The dataset includes performance...
In the scientific literature, multiple studies address the application of road extraction methodologies to a particular cartographic dataset. However, it is difficult for any study to perform a more reliable comparison among road extraction methodolo...
Datasets are important for researchers to build models and test how these perform, as well as to reproduce research experiments from others. This data paper presents the NILM Performance Evaluation dataset (NILMPEds), which is aimed primarily at rese...
Epitope prediction based on random peptide library screening has become a focus as a promising method in immunoinformatics research. Some novel software and web-based servers have been proposed in recent years and have succeeded in given test cases....
Organ-on-a-chip (OOC) technology has emerged as a groundbreaking approach for emulating the physiological environment, revolutionizing biomedical research, drug development, and personalized medicine. OOC platforms offer more physiologically relevant...
Unconfined Compressive Strength (UCS) of stabilized soils is commonly used for evaluating the effectiveness of soil improvement techniques. Achieving target UCS values through conventional trial-and-error approaches requires extensive laboratory expe...
In this study, based on total column ozone observations from eight Antarctic stations, we evaluate the applicability of ERA5, C3S-MSR, MERRA-2, and JRA-55 reanalysis datasets and the NIWA-BS merged satellite dataset, in terms of interannual variation...
The integration of dynamic hand gesture recognition in computer vision-based systems promises enhanced human–computer interaction, providing a natural and intuitive way of communicating. However, achieving real-time performance efficiency is a...
The number of global precipitation datasets (PPs) is on the rise and they are commonly used for hydrological applications. A comprehensive evaluation on their performance in hydrological modeling is required to improve their performance. This study c...
The lack of observed data makes research on the cryosphere and ecology extremely difficult, especially in Central Asia’s hilly regions. Before their direct hydroclimatic uses, the performance study of gridded precipitation datasets (GPDS) is of...
Due to the scarcity of meteorological stations on the Tibetan Plateau (TP), owing to the high altitude and harsh climate, studies often resort to satellite, reanalysis, and merged multi-source precipitation data. This necessitates an evaluation of TP...
As the Pamir Plateau is known as the “Water Tower of Central Asia”, accurate precipitation dataset is essential for the study of climate and hydrology in this region. Based on the monthly precipitation observations from 268 meteorological...
The existence of several gridded precipitation products (GPP) has facilitated studies related to climate change, climate modeling, as well as a better understanding of the physical processes underpinning this key variable. Due to complexities in esti...
Hydrological modeling has always been a challenge in the data-scarce watershed, especially in the areas with complex terrain conditions like the inland river basin in Central Asia. Taking Bosten Lake Basin in Northwest China as an example, the accura...
Global land use/cover change (LUCC) datasets are essential for quantitatively assessing the impacts of LUCC on global change, but many uncertainties in existing global datasets seriously hamper climate modeling. Evaluating the reliability of existing...
Air temperature and precipitation are two important meteorological factors affecting the earth’s energy exchange and hydrological process. High quality temperature and precipitation forcing datasets are of great significance to agro-meteorology...
Multi-source soil moisture (SM) products provide a vigorous tool for the estimation of soil moisture on a large scale, but it is crucial to carry out the evaluation of those products before further application. In the present work, an evaluation fram...
Sustainable water quality data are important for understanding historical variability and trends in river regimes, as well as the impact of industrial waste on the health of aquatic ecosystems. Sustainable water management practices heavily depend on...
Developing robust and reliable models for Named Entity Recognition (NER) in the Russian language presents significant challenges due to the linguistic complexity of Russian and the limited availability of suitable training datasets. This study introd...
Food extrusion is a widely used processing technique that transforms raw ingredients into structured food products—foods with well-defined textures, shapes, and functionalities—through mechanical shear and thermal energy. Despite its broa...
Steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) systems have been extensively researched over the past two decades, and multiple sets of standard datasets have been published and widely used. However, there are...
Cybersecurity is an arms race, with both the security and the adversaries attempting to outsmart one another, coming up with new attacks, new ways to defend against those attacks, and again with new ways to circumvent those defences. This situation c...
The advancement of super-resolution and sharpening algorithms for satellite images has significantly expanded the potential applications of remote sensing data. In the case of Sentinel-2, despite significant progress, the lack of standardized dataset...
Evidence from recent research shows that automatic visual evaluation (AVE) of photographic images of the uterine cervix using deep learning-based algorithms presents a viable solution for improving cervical cancer screening by visual inspection with...
Potential evapotranspiration (PET) is used in many hydrological models to estimate actual evapotranspiration. The calculation of PET by the Food and Agriculture Organization of the United Nations (FAO) Penman–Monteith method requires data for s...
With the rapid development of large visual language models (LVLMs) and multimodal large language models (MLLMs), these models have demonstrated strong performance in various multimodal tasks. However, alleviating the generation of hallucinations rema...
Cybersecurity has become one of the focuses of organisations. The number of cyberattacks keeps increasing as Internet usage continues to grow. As new types of cyberattacks continue to emerge, researchers focus on developing machine learning (ML)-base...
Information Retrieval is not any more exclusively about document ranking. Continuously new tasks are proposed on this and sibling fields. With this proliferation of tasks, it becomes crucial to have a cheap way of constructing test collections to eva...
High-resolution meteorological data products are crucial for agrometeorological studies. Here, we study the accuracy of an important gridded dataset, the near-surface temperature dataset from the 5 km × 5 km resolution China dataset of meteorol...
With the accelerating pace of global warming, the imperative of selecting robust, long-term drought monitoring tools is becoming increasingly pronounced. In this study, we computed the Standardized Precipitation Evapotranspiration Index (SPEI) at bot...
Structural health monitoring and condition assessment of existing bridge decks is a growing challenge. Conventional manned inspections are costly, labor-intensive, and often risky to execute. Sub-surface delamination, a leading cause of deck replacem...
The application of object detection technology has a positive auxiliary role in advancing the intelligence of bird recognition and enhancing the convenience of bird field surveys. However, challenges arise due to the absence of dedicated bird dataset...
Face recognition has become a major research area due to the rapid growth of intelligent software applications. However, reliable face identification remains challenging because human facial features vary significantly under different conditions. Ori...
The development of speech technology requires large amounts of data to estimate the underlying models. Even when relying on large multilingual pre-trained models, some amount of task-specific data on the target language is needed to fine-tune those m...
In the age of abundant digital content, children and adolescents face the challenge of developing new information literacy competencies, particularly those pertaining to online inquiry, in order to thrive academically and personally. This article add...
Millimeter-wave (MMW) 3-D imaging technology is becoming a research hotspot in the field of safety inspection, intelligent driving, etc., due to its all-day, all-weather, high-resolution and non-destruction feature. Unfortunately, due to the lack of...
This study focuses on the construction and evaluation of a high-quality Chinese Manchu music dataset designed to facilitate Artificial Intelligence (AI) research and applications within cultural heritage and ethnomusicology. Through a systematic coll...
We introduce an emotional stimuli detection task that targets extracting emotional regions that evoke people’s emotions (i.e., emotional stimuli) in artworks. This task offers new challenges to the community because of the diversity of artwork...
Site-specific weed management employs image data to generate maps through various methodologies that classify pixels corresponding to crop, soil, and weed. Further, many studies have focused on identifying specific weed species using spectral data. N...
Corners are an important kind of image feature and play a crucial role in solving various tasks. Over the past few decades, a great number of corner detectors have been proposed. However, there is no benchmark dataset with labeled ground-truth corner...
The concept of searching and localizing vehicles from live traffic videos based on descriptive textual input has yet to be explored in the scholarly literature. Endowing Intelligent Transportation Systems (ITS) with such a capability could help solve...
In recent years, we have seen a large growth in the number of applications which use deep learning-based object detectors. Autonomous driving assistance systems (ADAS) are one of the areas where they have the most impact. This work presents a novel s...
Micro-expression is the involuntary emotion of the human that reflects the genuine feelings that cannot be hidden. Micro-expression is exhibited by facial expressions that last for a short duration and have very low intensity. Because of these reason...
This study analyzed the applicability of five long-term precipitation datasets in the Hang-Jia-Hu Plain of eastern China based on meteorological observation data. The accuracy of each dataset at different time scales (yearly, monthly) was analyzed. B...
Lightweight vision models are widely deployed in mobile and embedded systems, where strict computational and memory budgets demand compact architectures. However, their evaluation remains dominated by ImageNet—a single, large natural-image data...
In social interactions, people who are perceived as competent win more chances, tend to have more opportunities, and perform better in both personal and professional aspects of their lives. However, the process of evaluating competence is still poorl...
Background: Melanoma is one of the most lethal skin cancers, with survival rates largely dependent on early detection, yet diagnosis remains difficult because of its visual similarity to benign nevi. Convolutional neural networks have achieved strong...
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