Citizen Visual Search Engine: Detection and Curation of Urban Objects

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Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

These are pytorch model weights for the angiopy-segmentation deep learning model, descriped in a paper published in 2024 in the International Journal of Cardiology: AngioPy segmentation: An open-source, user-guided deep learning tool for coronary artery se ...

There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

Deep metric learning (DML) has shown to be effective for content-based image retrieval (CBIR) in remote sensing (RS). Most of the DML methods for CBIR rely on a high number of annotated images to accurately learn model parameters of deep neural networks (D ...

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

Combining the excellent thermal and electrical properties of Cu with the high abrasion resistance and thermal stability of W, Cu-W nanoparticle-reinforced metal matrix composites and nano-multilayers are finding applications as brazing fillers and shieldin ...

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

The rates of tropical deforestation remain high, resulting in carbon emissions, biodiversity loss, and impacts on local communities. To design effective policies to tackle this, it is necessary to know what the drivers behind deforestation are. Since drive ...

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

A critical operational challenge in Mobility-on-demand systems is the problem of imbalance between vehicle supply and passenger demand. However, conventional model-based methods require accurate parametric system models with complex nonlinear dynamics that ...

While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the sci ...

The perception of autonomous vehicles using radars has attracted increased research interest due its ability to operate in fog and bad weather. However, training radar models is hindered by the cost and difficulty of annotating largescale radar data. To ov ...

Electronic skins are expected to replicate a human-like tactile sense, which significantly detects surface information, including geometry, material, and temperature. Although most texture features can be sensed in the horizontal direction, the lack of eff ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

With global environmental change and quality of life issues at the forefront of international discussions today, urban development strategies and policies are often framed around various sustainability or liveability goals. Regardless of the sustainability ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

Blood pressure (BP) is a crucial indicator of cardiovascular health. Hypertension is a common life-threatening condition and a key factor of cardiovascular diseases (CVDs). Identifying abnormal BP fluctuations can allow for early detection and management o ...

The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of density functional theory (DFT). However, running large simulation cells with DFT is computationally demanding, wh ...

Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven si ...

CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode act ...

Citizen Visual Search Engine: Detection and Curation of Urban Objects

Chat with Graph Search

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

PyTorch 2 Model for the prediction of single-artery segmentations for "AngioPy segmentation: An open-source, user-guided deep learning tool for coronary artery segmentation"

Transfer learning application of self-supervised learning in ARPES

Annotation Cost-Efficient Active Learning for Deep Metric Learning-Driven Remote Sensing Image Retrieval

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Machine learning potential for the Cu-W system

Validating functional redundancy with mixed generative adversarial networks

Mapping drivers of tropical forest loss with satellite image time series and machine learning

Machine Learning for Modeling Stock Returns

Data-enabled Predictive Control for Empty Vehicle Rebalancing

The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry

Bootstrapping Autonomous Driving Radars with Self-Supervised Learning

All-Printed Finger-Inspired Tactile Sensor Array for Microscale Texture Detection and 3D Reconstruction

Aggregating Spatial and Photometric Context for Photometric Stereo

Urban sustainability assessment through spatial lenses: turning the spotlight on the local neighbourhood unit

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Data-driven approaches for non-invasive cuffless blood pressure monitoring

Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

Robustness of Local Predictions in Atomistic Machine Learning Models

Brain dynamics uncovered using a machine-learning algorithm