Artificial Intelligence Based Methods for Smart and Sustainable Urban Planning: A Systematic Survey

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Unmanned Aerial Vehicle (UAV) Cross-View Geo-Localization (CVGL) poses significant challenges due to the substantial view discrepancies between oblique UAV images and overhead satellite images. Existing methods heavily rely on supervised learning with labe ...

Spatial proteomics technologies have transformed our understanding of complex tissue architectures by enabling simultaneous analysis of multiple molecular markers and their spatial organization. The high dimensionality of these data, varying marker combina ...

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non i.i.d (not independent or identically distributed). This provides a significant challenge as the data of the other clie ...

Customer Satisfaction (CS) in call centers influences customer loyalty and the company's reputation. Traditionally, CS evaluations were conducted manually or with classical machine learning algorithms; however, advancements in deep learning have led to aut ...

We introduce the concept of "universal"password model - a password model that, once pre-trained, can automatically adapt its guessing strategy based on the target system. To achieve this, the model does not need to access any plaintext passwords from the t ...

The development of biophysical models for clinical applications is rapidly advancing in the research community, thanks to their predictive nature and their ability to assist the interpretation of clinical data. However, high-resolution and accurate multi-p ...

In some areas of Antarctica, blue-colored bare ice is exposed at the surface. These blue ice areas (BIAs) can trap meteorites or old ice and are vital for understanding the climatic history. By combining multi-sensor remote sensing data (MODIS, RADARSAT-2, ...

This note describes a method to train a Neural Network so that it approximates a control Lyapunov function for a nonlinear system in affine form. The network is trained in a physics-informed fashion, as the training data are generated by enforcing the nega ...

This work presents a recommendation system for metal-organic frameworks (MOFs) inspired by online content platforms. By leveraging the unsupervised Doc2Vec model trained on document-structured intrinsic MOF characteristics, the model embeds MOFs into a hig ...

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

The Serviceability Limit States (SLS) of reinforced concrete structures, where cracking and deflection limits are verified in the design process, are directly related to time-dependent properties of concrete. In this study, the effects of creep and shrinka ...

The Eurocode 2 for the design of concrete structures (EN1992-1-1:2004) is undergoing a revision that will lead to the publication of the second generation of this code to be used across all CEN member countries. Therefore, the impact of the code will reach ...

High-tech industries power the modern digital world, but their supply chains are particularly vulnerable to geopolitical and economic disruption. Urgent action is needed to improve supply-chain resilience. ...

Neural machine translation (MT) and text generation have recently reached very high levels of quality. However, both areas share a problem: in order to reach these levels, they require massive amounts of data. When this is not present, they lack generaliza ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

It is hard to overestimate the role of winter roads in the land logistics of the northern regions. In recent years, climate change has not only significantly reduced the service life of winter roads, but also made them less predictable. This forces transpo ...

The use of Internet of Things (IoT) sensors for air pollution monitoring has significantly increased, resulting in the deployment of low-cost sensors. Despite this advancement, accurately calibrating these sensors in uncontrolled environmental conditions r ...

Artificial Intelligence Based Methods for Smart and Sustainable Urban Planning: A Systematic Survey

Chattez avec Graph Search

Unsupervised Multi-view UAV Image Geo-localization via Iterative Rendering

Abstract B037: AI-powered virtual tissues from spatial proteomics for clinical diagnostics and biomedical discovery

Data Heterogeneity in Linear Distributed Estimation and Learning

Cross-transfer Knowledge between Speech and Text Encoders to Evaluate Customer Satisfaction

Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data

Physics-informed neural network estimation of material properties in soft tissue nonlinear biomechanical models

Where the White Continent Is Blue: Deep Learning Locates Bare Ice in Antarctica

Stabilization of nonlinear systems by neural Lyapunov approximators and Sontag's formula

Deep learning-based recommendation system for metal-organic frameworks (MOFs)

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Privatized graph federated learning

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Verification of deflections and cracking of RC flat slabs with numerical and analytical approaches

A Discussion on the Reliability of prEN1992-1-1:2021 Shear Strength Provisions for Fibre Reinforced Concrete Members Without Shear Reinforcement

Building resilience in high-tech supply chains

Regularization Techniques for Low-Resource Machine Translation

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

On the possibility of extending the service life of winter roads using renewable energy sources

Spatial-Temporal Graph Attention Fuser for Calibration in IoT Air Pollution Monitoring Systems