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

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We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

Direct photolysis and indirect photolysis are important abiotic processes in aquatic environments through which plastics can be transformed physically and chemically. Transport of biodegradable plastics in water is influenced by vertical mixing and turbule ...

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...

Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...

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 ...

A central question of machine learning is how deep nets manage to learn tasks in high dimensions. An appealing hypothesis is that they achieve this feat by building a representation of the data where information irrelevant to the task is lost. For image da ...

The management of plastic waste is a growing concern that can harm wildlife and ecosystems, and its end-of-life policies are key to mitigating plastic environmental impact. This work presents a decision-making methodology for the thermal and material valor ...

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really gener ...

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

Deep learning models for learning analytics have become increasingly popular over the last few years; however, these approaches are still not widely adopted in real-world settings, likely due to a lack of trust and transparency. In this paper, we tackle th ...

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 ...

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

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

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Detecting Anomalies and Obstacles in Road Scenes

Photodegradation of biodegradable plastics in aquatic environments: Current understanding and challenges

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Rigidity-Aware Detection for 6D Object Pose Estimation

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

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

How deep convolutional neural networks lose spatial information with training

On the role of system integration in plastic waste management

Why is the winner the best?

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design

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

Probabilistic methods for neural combinatorial optimization