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

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Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as ...

Multi-object multi-part scene segmentation is a challenging task whose complexity scales exponentially with part granularity and number of scene objects. To address the task, we propose a plug-and-play approach termed OLAF. First, we augment the input (RGB ...

Patch-based matching is a technique meant to measure the disparity between pixels in a source and target image and is at the core of various methods in computer vision. When the subpixel disparity between the source and target images is required, the cost ...

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 ...

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 ...

Large-scale electron microscopy (EM) has enabled the reconstruction of brain connectomes at the synaptic level by serially scanning over massive areas of sample sections. The acquired big EM data sets raise the great challenge of image mosaicking at high a ...

Wildlife observation with camera traps has great potential for ethology and ecology, as it gathers data non-invasively in an automated way. However, camera traps produce large amounts of uncurated data, which is time-consuming to annotate. Existing methods ...

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 ...

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 ...

Statistical learning algorithms provide a generally-applicable framework to sidestep time-consuming experiments, or accurate physics-based modeling, but they introduce a further source of error on top of the intrinsic limitations of the experimental or the ...

Quantum state reconstruction using Neural Quantum States has been proposed as a viable tool to reduce quantum shot complexity in practical applications, and its advantage over competing techniques has been shown in numerical experiments focusing mainly on ...

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 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 ...

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 ...

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 ...

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 ...

The use of aerial vehicles for exploration and data collection has the potential to significantly aid environmental monitoring in environments which are dangerous and hard to navigate. However, within these environments navigation can often be restricted b ...

This study evaluates and compares several machine learning methods on the effects of different parameters in lead adsorption capacity. pH, contact time, adsorbent dosage and initial lead concentration were considered as inputs and adsorption capacity was r ...

The world's cities are facing various challenges such as rapid urbanization, poverty, climate change, pollution, sustainable and inclusive development. Building futuristic smart and sustainable cities is proving to be a response to these challenges. Recent ...

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

Chattez avec Graph Search

Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond

OLAF: A Plug-and-Play Framework for Enhanced Multi-object Multi-part Scene Parsing

Generalized Closed-form Formulae for Feature-based Subpixel Alignment in Patch-based Matching

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

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

Two-stage error detection to improve electron microscopy image mosaicking

WildCLIP: Scene and Animal Attribute Retrieval from Camera Trap Data with Domain-Adapted Vision-Language 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

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

Uncertainty quantification by direct propagation of shallow ensembles

Empirical Sample Complexity of Neural Network Mixed State Reconstruction

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

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

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

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

Regularization Techniques for Low-Resource Machine Translation

Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial Robot

Investigation of effective processes parameters on lead (II) adsorption from wastewater by biochar in mild air oxidation pyrolysis process

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