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

Related publications (20)

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

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 ...

2025

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

Eeshaan Jain, Johann Clemens Werner Wenckstern, Charlotte Cäcilie Gertrud Bunne

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 ...

American Association for Cancer Research (AACR)2025

Data Heterogeneity in Linear Distributed Estimation and Learning

Aditya Pradeep

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 ...

EPFL2025

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

Tilak Purohit

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 ...

International Speech Communication Association2024

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

Carmela González Troncoso, Dario Pasquini

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 ...

Institute of Electrical and Electronics Engineers Inc.2024

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

Alfio Quarteroni

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 ...

SPRINGER2024

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

Devis Tuia, Marc Conrad Russwurm

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, ...

Amer Geophysical Union2024

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

Adriano Mele

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 ...

Institute of Electrical and Electronics Engineers Inc.2024

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

Berend Smit, Kevin Maik Jablonka, Xiaoqi Zhang

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 ...

Royal Soc Chemistry2024

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

Geovani Rizk, Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Youssef Allouah

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 ...

2023

Privatized graph federated learning

Ali H. Sayed, Stefan Vlaski, Elsa Rizk

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 ...

SPRINGER2023

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

Silvestro Micera, Simone Romeni

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 ...

IOP Publishing Ltd2023

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

Aurelio Muttoni

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 ...

ELSEVIER SCI LTD2023

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

Miguel Fernández Ruiz

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 ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Building resilience in high-tech supply chains

Ankita Singhvi

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. ...

NATURE PORTFOLIO2023

Regularization Techniques for Low-Resource Machine Translation

Alejandro Ramírez Atrio

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 ...

EPFL2023

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

Gulnaz Ganeeva

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 ...

EPFL2023

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

Christophe Ballif, Nicolas Würsch, Laure-Emmanuelle Perret Aebi, Marine Dominique Cauz

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 ...

2023

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

Elizaveta Sharaborova

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 ...

2023

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

Olga Fink, Mengjie Zhao, Keivan Faghih Niresi

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 ...

Institute of Electrical and Electronics Engineers2023