Results 61 to 70 of about 8,937 (214)

Hierarchical Metric Learning for Optical Remote Sensing Scene Categorization

, 2018
We address the problem of scene classification from optical remote sensing (RS) images based on the paradigm of hierarchical metric learning. Ideally, supervised metric learning strategies learn a projection from a set of training data points so as to ...
Banerjee, Biplab, Goel, Akashdeep, Pizurica, Aleksandra   +2 more
core   +1 more source

Deep Learning Based Panchromatic2RGB Image Generation from VHR Images

Mersin Photogrammetry Journal
Image colorization is the process of obtaining colored images by assigning RGB color values to a grayscale or panchromatic image. This technique has an important place in the field of computer vision because colored images provide a better visual experience and are widely used in areas such as image recognition and object detection.
Ceyda Nigar Ünyılmaz, Bahadır Kulavuz, Tolga Bakırman, Bülent Bayram   +3 more
openaire   +2 more sources

AUTOMATIC DETECTION OF GREY INFRASTRUCTURE BASED ON VHR IMAGE [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
Abstract. Grey infrastructure is an integral part of the urban environment. Continuous modernization of architecture, construction, routes or services in that region leads to more and more new grey infrastructure appearing. The reason for this are constant migrations of people, dissemination of a healthy lifestyle or improvement of its level.
openaire   +3 more sources

Ground‐truthing of satellite imagery to assess seabird colony size: A test using Adélie penguins

Remote Sensing in Ecology and Conservation, EarlyView.
Adélie penguin colony size can be estimated from space using very high‐resolution (VHR; 0.3–0.6 m resolution) satellite imagery due to the contrast between their guano stain and the surrounding terrain. Our study assessed the utility of VHR imagery for making indirect assessments of changes in colony size.
Alexandra J. Strang, Dean P. Anderson, Esme Robinson, Grant Ballard, Annie E. Schmidt, David G. Ainley, Kerry Barton, Fiona Shanhun, Elissa Z. Cameron, Michelle A. LaRue   +9 more
wiley   +1 more source

Discovery of a First‐in‐Class Covalent Allosteric SHP1 Inhibitor with Immunotherapeutic Activity

Angewandte Chemie, Volume 138, Issue 7, 9 February 2026.
A covalent allosteric inhibitor M029 was discovered for SHP1, a novel target for immunotherapy. M029 binds to a cryptic Cys remote from the active site, exhibits robust target engagement, and blocks tumor progression by stimulating antitumor immune response.
Zihan Qu, Frederick Nguele Meke, Zheng Zhang, Aaron D. Krabill, Christine S. Muli, Brenson A. Jassim, Jiajun Dong, Quyen D. Nguyen, Yunpeng Bai, Jinyue Li, Yiming Miao, Bardia Asadi, Levi M. Johnson, Jinmin Miao, Darci J. Trader, W. Andy Tao, Zhong‐Yin Zhang   +16 more
wiley   +2 more sources

Texture Retrieval from VHR Optical Remote Sensed Images Using the Local Extrema Descriptor with Application to Vineyard Parcel Detection

Remote Sensing, 2016
In this article, we develop a novel method for the detection of vineyard parcels in agricultural landscapes based on very high resolution (VHR) optical remote sensing images.
Minh-Tan Pham, Grégoire Mercier, Oliver Regniers, Julien Michel   +3 more
doaj   +1 more source

Transformer-Based Semantic Segmentation for Extraction of Building Footprints from Very-High-Resolution Images

Sensors, 2023
Semantic segmentation with deep learning networks has become an important approach to the extraction of objects from very high-resolution remote sensing images.
Jia Song, A-Xing Zhu, Yunqiang Zhu
doaj   +1 more source

Wall‐to‐wall Amazon forest height mapping with Planet NICFI, Aerial LiDAR, and a U‐Net regression model

Remote Sensing in Ecology and Conservation, EarlyView.
Tree canopy height is a key indicator of forest biomass and structure, yet accurate mapping across the Amazon remains challenging. Here, we generated a canopy height map of the Amazon forest at ~4.8 m resolution using Planet NICFI imagery and a deep learning U‐Net model trained with airborne LiDAR data.
Fabien H. Wagner, Ricardo Dalagnol, Griffin Carter, Mayumi C. M. Hirye, Shivraj Gill, Le Bienfaiteur Sagang Takougoum, Samuel Favrichon, Michael Keller, Jean P. H. B. Ometto, Lorena Alves, Cynthia Creze, Stephanie P. George‐Chacon, Shuang Li, Zhihua Liu, Adugna Mullissa, Yan Yang, Erone G. Santos, Sarah R. Worden, Martin Brandt, Philippe Ciais, Stephen C. Hagen, Sassan Saatchi   +21 more
wiley   +1 more source

A Generic FCN-Based Approach for the Road-Network Extraction From VHR Remote Sensing Images – Using OpenStreetMap as Benchmarks

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
As one road network is often the backbone in a geo-spatial dataset, capturing and/or updating the road networks using remote sensing imagery play an important role in traffic management, urban planning, vehicle navigation, and emergency management. Along
Deng Pan, Meng Zhang, Bo Zhang
doaj   +1 more source

Lacking data? No worries! How synthetic images can alleviate image scarcity in wildlife surveys: A case study with muskox (Ovibos moschatus)

Remote Sensing in Ecology and Conservation, EarlyView.
This study investigates the integration of synthetic imagery, created with diffusion‐based models, to supplement limited training data and improve muskox (Ovibos moschatus) detection in zero‐shot (ZS) and few‐shot (FS) settings. ZS models detected more than 80% of muskoxen in real images, confirming the potential of synthetic data as a substitute for ...
Simon Durand, Samuel Foucher, Alexandre Delplanque, Joëlle Taillon, Jérôme Théau   +4 more
wiley   +1 more source