Drone‐Based Solar Cell Inspection With Autonomous Deep Learning

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

As the share of electricity generation from non-dispatchable sources like wind and photovoltaics grows, so does the need for demand response to stabilize the grid. Since the electricity consumption of heat pumps in buildings is both substantial and flexibl ...

How does the brain generate behavioral responses from sensory stimuli? This sensor-to-motor transformation is a fundamental question in systems neuroscience. While recent experiments have highlighted the complexity of neural representations across the cere ...

The complexity of modern control systems necessitates architectures that achieve high performance while ensuring robust stability, particularly for nonlinear systems. In this work, we tackle the challenge of designing output-feedback controllers to boost t ...

Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like complex architectures customized for a specific dataset and inefficient multimoda ...

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 ...

This study presents the design and performance evaluation of a solar-driven water desalination system based on forward osmosis (FO) with thermally responsive ionic liquids (ILs). FO is a two-step process involving dilution of the ILs with water, followed b ...

This manuscript details and extends the system identification methods leveraging the backpropagation (SIMBa) toolbox presented in previous work, which uses well-established machine learning tools for discrete-time linear multistep-ahead state-space system ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

This thesis reports on the study and use of low temperature processes for the deposition of indium gallium nitride (InGaN) thin films in order to alleviate some of the present drawbacks of its monolitic deposition on silicon for photovoltaic applications. ...

The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition o ...

Non-linear partial differential Kolmogorov equations are successfully used to describe a wide range of time dependent phenomena, in natural sciences, engineering or even finance. For example, in physical systems, the Allen-Cahn equation describes pattern f ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

The high computational costs of deep convolutional neural networks hinder their deployment in real-world applications, including pulmonary nodule detection from CT scans where large 3D image sizes amplify the issue. This paper presents a novel 3D method to ...

The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Here, remote sensing can provide reliable estimates of plastic pollution by regularly monitoring and d ...

Organic-inorganic perovskite solar cells have achieved an impressive power conversion efficiency of up to 25.6% and 24.8%, respectively, for single and multijunction tandem architectures due to the huge progress made in the rational design and development ...

Deep learning-based approaches to delineating 3D structure depend on accurate annotations to train the networks. Yet in practice, people, no matter how conscientious, have trouble precisely delineating in 3D and on a large scale, in part because the data i ...

Data-driven approaches based on high-throughput capabilities and machine learning hold promise in revolutionizing human-centred materials discovery for sustainability and decarbonization. This Review examines the strengths and limitations of different trad ...

Solar photovoltaic (PV) is the most rapidly expanding renewable resource worldwide. Yet, its full potential may be hindered by mismatches with market demand and correlated production profiles. In this research, we explore a case study of innovative PV plac ...

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We im ...

Drone‐Based Solar Cell Inspection With Autonomous Deep Learning

Chattez avec Graph Search

A commissioning-oriented approach to data-driven modeling of buildings with heat pumps for predictive demand response

Capturing behavioral and neural variability in multi-area spiking neuronal network models

Parametrizations of all stable closed-loop responses: From theory to neural network control design

Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting

Aggregating Spatial and Photometric Context for Photometric Stereo

Performance modeling and cost optimization of a solar desalination system using forward osmosis with energy storage

SIMBa: System Identification Methods Leveraging Backpropagation

Reliable data-driven decision-making through optimal transport

III-V Nitride Semiconductors Deposited At Low Temperature For Photovoltaic Applications

Euclid: Identification of asteroid streaks in simulated images using deep learning

Solving Non-linear Kolmogorov Equations in Large Dimensions by Using Deep Learning: A Numerical Comparison of Discretization Schemes

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Efficient Lung Nodule Detection via 3D Deep Learning with Shifted Convolutions

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

Large-scale detection of marine debris in coastal areas with Sentinel-2

Charge transport materials for mesoscopic perovskite solar cells

Adjusting the Ground Truth Annotations for Connectivity-Based Learning to Delineate

Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

Optimized market value of alpine solar photovoltaic installations

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs