High-resolution population maps derived from Sentinel-1 and Sentinel-2

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Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremor and seizure detection) as well as prosthetic devices (for motor and communication recovery). By integratin ...

Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence and is limited ...

Transforaminal lumbar interbody fusion (TLIF) is a commonly used technique for treating lumbar degenerative diseases. In this study, we developed a fully computer-supported pipeline to predict both the cage height and the degree of lumbar lordosis subtract ...

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

We introduce a novel human-centric deep reinforcement learning recommender system designed to co-optimize energy consumption, thermal comfort, and air quality in commercial buildings. Existing approaches typically optimize these objectives separately or fo ...

Electrochemical batteries are ubiquitous devices in our society. When employed in mission-critical applications, the ability to precisely predict their end-of-discharge under highly variable operating conditions is of paramount importance in order to suppo ...

Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...

In this dissertation, I develop theory and evidence to argue that new technologies are central to how firms organize to create and capture value. I use computational methods such as reinforcement learning and probabilistic topic modeling to investigate thr ...

In recent years, the importance of electric mobility has increased in response to climate change. The fast-growing deployment of electric vehicles (EVs) worldwide is expected to decrease transportation-related emissions, facilitate the integration of renew ...

It has been experimentally observed that the efficiency of distributed training with stochastic gradient (SGD) depends decisively on the batch size and—in asynchronous implementations—on the gradient staleness. Especially, it has been observed that the spe ...

Objective.Mobile Brain/Body Imaging (MoBI) frameworks allowed the research community to find evidence of cortical involvement at walking initiation and during locomotion. However, the decoding of gait patterns from brain signals remains an open challenge. ...

Permission systems are the main defense that mobile platforms, such as Android and iOS, offer to users to protect their private data from prying apps. However, due to the tension between usability and control, such systems have several limitations that oft ...

Phonological features extracted by neural network have shown interesting potential for low bit rate speech vocoding. The span of phonological features is wider than the span of phonetic features, and thus fewer frames need to be transmitted. Moreover, the ...

As a measurement, built density (coefficient of land surface to be built and total floor space) has been the object of numerous researches on urban morphology and architectural forms during the twentieth century. However, for the last ten years, its sensor ...

High-resolution population maps derived from Sentinel-1 and Sentinel-2

Chat with Graph Search

Integrating Neural Interfaces with Machine Learning: Enabling Self-Sufficient and Ubiquitous Prosthetic and Diagnostic Devices

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

Development of End-to-End Artificial Intelligence Models for Surgical Planning in Transforaminal Lumbar Interbody Fusion

The multimodality cell segmentation challenge: toward universal solutions

A multi-task deep reinforcement learning-based recommender system for co-optimizing energy, comfort, and air quality in commercial buildings with humans-in-the-loop

Ageing-aware battery discharge prediction with deep learning

End-to-end kernel learning via generative random Fourier features

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Deep reinforcement learning control of electric vehicle charging in the presence of photovoltaic generation

Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates

Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network

SmarPer: Context-Aware and Automatic Runtime-Permissions for Mobile Devices

On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding

Densité et logement collectif : innovations architecturales et urbaines dans la Suisse contemporaine