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Typically, the detection of marine debris relies on in-situ campaigns that are characterized by huge human effort and limited spatial coverage. Following the need of a rapid solution for the detection of floating plastic, methods based on…

计算机视觉与模式识别 · 计算机科学 2024-08-20 Muhammad Alì , Francesca Razzano , Sergio Vitale , Giampaolo Ferraioli , Vito Pascazio , Gilda Schirinzi , Silvia Ullo

Pollution and climate change are some of the biggest challenges that humanity is facing. In such a context, efficient recycling is a crucial tool for a sustainable future. This work is aimed at creating a system that can classify different…

机器学习 · 计算机科学 2021-10-26 Anton Persson , Niklas Dymne , Fernando Alonso-Fernandez

With the global issue of plastic debris ever expanding, it is about time that the technology industry stepped in. This study aims to assess whether deep learning can successfully distinguish between marine life and man-made debris…

机器学习 · 计算机科学 2022-12-14 Zoe Moorton , Zeyneb Kurt , Wai Lok Woo

Currently the extent of nanoplastic in the environment can only be estimated by extrapolation from the plastic waste that can be detected. To be able to quantify the whole extent of the problem, detection methods have to be developed that…

光学 · 物理学 2025-11-12 Ambika Shorny , Fritz Steiner , Helmut Hörner , Sarah M. Skoff

The widespread use of Exogenous Organic Matter in agriculture necessitates monitoring to assess its effects on soil and crop health. This study evaluates optical Sentinel-2 satellite imagery for detecting digestate application, a practice…

计算机视觉与模式识别 · 计算机科学 2025-12-01 Andreas Kalogeras , Dimitrios Bormpoudakis , Iason Tsardanidis , Dimitra A. Loka , Charalampos Kontoes

The detection and classification of exfoliated two-dimensional (2D) material flakes from optical microscope images can be automated using computer vision algorithms. This has the potential to increase the accuracy and objectivity of…

计算机视觉与模式识别 · 计算机科学 2026-02-06 Jan-Lucas Uslu , Alexey Nekrasov , Alexander Hermans , Bernd Beschoten , Bastian Leibe , Lutz Waldecker , Christoph Stampfer

We develop a 3D Eulerian model to study the transport and distribution of microplastics in the global ocean. Among other benefits that will be discussed in the paper, one unique feature of our model is that it takes into consideration the…

大气与海洋物理 · 物理学 2024-11-22 Zih-En Tseng , Yue Wu , Dimitris Menemenlis , Guangyao Wang , Chris Ruf , Yulin Pan

In the last several years, remote sensing technology has opened up the possibility of performing large scale building detection from satellite imagery. Our work is some of the first to create population density maps from building detection…

计算机视觉与模式识别 · 计算机科学 2017-07-28 Amy Zhang , Xianming Liu , Andreas Gros , Tobias Tiecke

With the increasing use of plastic, the challenges associated with managing plastic waste have become more challenging, emphasizing the need of effective solutions for classification and recycling. This study explores the potential of deep…

计算机视觉与模式识别 · 计算机科学 2024-12-31 Suman Kunwar , Banji Raphael Owabumoye , Abayomi Simeon Alade

The Copernicus Sentinel-2 program now provides multispectral images at a global scale with a high revisit rate. In this paper we explore the usage of convolutional neural networks for urban change detection using such multispectral images.…

计算机视觉与模式识别 · 计算机科学 2018-10-22 Rodrigo Caye Daudt , Bertrand Le Saux , Alexandre Boulch , Yann Gousseau

This paper presents methods to identify the plastic waste based on its resin identification code to provide an efficient recycling of post-consumer plastic waste. We propose the design, training and testing of different machine learning…

计算机视觉与模式识别 · 计算机科学 2020-11-17 Shivaank Agarwal , Ravindra Gudi , Paresh Saxena

This work utilizes a MobileNetV2 Convolutional Neural Network (CNN) for fast, mobile detection of satellites, and rejection of stars, in cluttered unresolved space imagery. First, a custom database is created using imagery from a synthetic…

计算机视觉与模式识别 · 计算机科学 2022-07-26 Jarred Jordan , Daniel Posada , David Zuehlke , Angelica Radulovic , Aryslan Malik , Troy Henderson

Garbage and waste disposal is one of the biggest challenges currently faced by mankind. Proper waste disposal and recycling is a must in any sustainable community, and in many coastal areas there is significant water pollution in the form…

计算机视觉与模式识别 · 计算机科学 2019-05-15 Matias Valdenegro-Toro

Convolutional neural networks (CNN) have been used efficiently in several fields, including environmental challenges. In fact, CNN can help with the monitoring of marine litter, which has become a worldwide problem. UAVs have higher…

计算机视觉与模式识别 · 计算机科学 2025-08-25 Ousmane Youme , Jean Marie Dembélé , Eugene C. Ezin , Christophe Cambier

We propose and evaluate the feasibility of a new strategy to search for planets via microlensing observations. This new strategy is designed to detect planets in "wide" orbits, i.e., with orbital separation, a, greater than ~1.5 R_E.…

天体物理学 · 物理学 2007-05-23 Rosanne Di Stefano , Richard A. Scalzo

There are 50 billion pieces of litter in the U.S. alone. Grass fields contribute to this problem because picnickers tend to leave trash on the field. We propose building a robot that can autonomously navigate, identify, and pick up trash in…

机器人学 · 计算机科学 2026-01-21 Christopher Kao , Akhil Pathapati , James Davis

Marine debris poses a significant ecological threat to birds, fish, and other animal life. Traditional methods for assessing debris accumulation involve labor-intensive and costly manual surveys. This study introduces a framework that…

计算机视觉与模式识别 · 计算机科学 2024-07-23 Raymond Wang , Nicholas R. Record , D. Whitney King , Tahiya Chowdhury

Plastic pollution in the aquatic environment has been assessed for many years by ocean waste collection expeditions around the globe or by river sampling. While the total amount of plastic produced worldwide is well documented, the amount…

软凝聚态物质 · 物理学 2024-01-17 Matthieu George , Frédéric Nallet , Pascale Fabre

Advances in Earth observation (EO) foundation models have unlocked the potential of big satellite data to learn generic representations from space, benefiting a wide range of downstream applications crucial to our planet. However, most…

The ANTARES collaboration propose to observe High Energy Cosmic Neutrinos using a Deep Sea Cherenkov detector. The sky survey with high energy neutrinos is complementary to the observations with photons. It is expected that this will shed a…

天体物理学 · 物理学 2012-08-27 ANTARES collaboration