Buscar recursos académicos

Abstract Publicly available, large-scale medical imaging datasets are crucial for developing and validating artificial intelligence (AI) models and conducting retrospective clinical research. However, multimodal datasets...

ABSTRACT Plant diseases are the cause of heavy losses of crop production and, therefore, a big contributor to food shortages. Identifying these diseases as early as possible is important to limit the negative effects tha...

Mathematics readiness at entry remains critical for success in first-year engineering programs, yet many institutions lack transparent, reusable tools to diagnose risk and design levelling policies. This study develops a...

Abstract Argument annotation in medical drug reviews is a challenging task due to noisy user-generated content, domain-specific terminology, and subjective expressions of medication efficacy and adverse effects. While ar...

The rapid proliferation of unmanned aerial vehicles (UAVs) has created an urgent need for robust detection & identification systems to ensure airspace security and safety. However, the scarcity of large-scale, div...

This study introduces an enhanced generalized progressive Type-II hybrid censoring scheme incorporating binomial random removals, which provides a more realistic alternative to fixed removal patterns commonly assumed in ...

As smart meter technology advances, advanced metering infrastructure (AMI) enables the collection of high-resolution energy consumption data, such as 15-minute interval electricity and gas usage. While anomaly detection ...

Question-answering (QA) has been a crucial NLP (Natural Language Processing) task for a long time. As an umbrella term, QA has multiple sub-tasks under its hood. Question classification (QC) is one of the most important ...

The validity of research findings critically depends on the selection of software samples. However, Mining Software Repositories studies often rely on outdated datasets and lack systematic, transparent procedures for rep...

Abstract Feature selection is a critical step in machine learning, as it helps minimize redundant features, thereby enhancing model performance and interpretability. In practice, partially labeled datasets are common. Wh...

Fault Detection and Diagnosis (FDD) is crucial for ensuring safe, reliable, and energy-efficient operation of collaborative robots, especially with the growth of Industry 4.0. Industrial robots are nonlinear, complex, an...

In the context of globalized food production, traceability is a key requirement in the fisheries sector, particularly for prepared and packaged fish products, where processing may hinder visual inspection and increase th...

Background The semideciduous Atlantic Forest is one of the most diverse ecosystems in the world with a great diversity of spiders. Most spider-related studies in this ecosystem focused on species richness and composition...

Water information systems (ISs) are essential for sustainable water management but are often constrained by fragmented, heterogeneous, and rapidly evolving data. Advances in generative artificial intelligence (GenAI), pa...

Abstract Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statist...

IntroductionThIntrusion Detection Systems (IDS) for Internet of Things (IoT) and edge environments require datasets with unambiguous labels, yet existing datasets often mix benign and malicious traffic within the same ca...

Aviation and meteorology are entwined disciplines, as aviation occurs in the atmosphere. Prevailing weather conditions at take-off are of utmost importance to aviation. This determines the payload of the aircraft and run...

The key component of contemporary biometric security systems is the accurate identification and validation of individuals using facial recognition technology. Advanced security systems can now be personalized through imp...

With the consolidation of deep learning in drug discovery, several novel algorithms for learning molecular representations have been proposed. Despite the interest of the community in developing new methods for learning ...

Pixel-level segmentation is critical for remote sensing applications, yet traditional supervised methods suffer from high annotation costs. While foundational vision models like CLIP and the Segment Anything Model (SAM) ...

In this paper, we propose a new visual tracking method in light of salience information and deep learning. Salience detection is used to exploit features with salient information of the image. Complicated representations...

Abstract Accurate and reliable wind power forecasting models are essential for the optimal dispatch of power systems. However, existing methods still face several challenges, including ineffective signal decomposition, l...

To date, various optimization algorithms have been used to design non-intuitive photonic structures with unconventional optical performance. Good training datasets facilitate the optimization process, particularly when a...

The clustering of small molecules implies the organization of a group of chemical structures into smaller subgroups with similar features. Clustering has important applications to sample chemical datasets or libraries in...