Results 51 to 60 of about 24,571,413 (390)
Subjective Saliency Model Driven by Multi-Cues Stimulus for Airport Detection
IEEE Access, 2019 Traditional saliency models designed for natural scene images usually use human visual characteristics to detect the target, but those salient areas in the remote sensing images (RSIs) may not be the targets we are really interested in.
Danpei Zhao +4 more
doaj +1 more source
Generalized Inpainting Method for Hyperspectral Image Acquisition
, 2015 A recently designed hyperspectral imaging device enables multiplexed acquisition of an entire data volume in a single snapshot thanks to monolithically-integrated spectral filters.
Blanch, Carolina +6 more
core +1 more source
In Defense of Classical Image Processing: Fast Depth Completion on the CPU [PDF]
Canadian Conference on Computer and Robot Vision, 2018 With the rise of data driven deep neural networks as a realization of universal function approximators, most research on computer vision problems has moved away from handcrafted classical image processing algorithms.
Jason Ku +2 more
semanticscholar +1 more source
Remote Sensing, 2017 Physically-based atmospheric correction of optical Earth Observation satellite data is used to accurately derive surface biogeophysical parameters free from the atmospheric influence. While water vapor or surface pressure can be univocally characterized,
Jorge Vicent +4 more
doaj +1 more source
Study on Image Filtering -- Techniques, Algorithm and Applications [PDF]
arXiv, 2022 Image processing is one of the most immerging and widely growing techniques making it a lively research field. Image processing is converting an image to a digital format and then doing different operations on it, such as improving the image or extracting various valuable data. Image filtering is one of the fascinating applications of image processing.
arxiv
Deep Decomposition Network for Image Processing: A Case Study for Visible and Infrared Image Fusion [PDF]
arXiv, 2021 Image decomposition is a crucial subject in the field of image processing. It can extract salient features from the source image. We propose a new image decomposition method based on convolutional neural network. This method can be applied to many image processing tasks.
arxiv
Selective focus saliency model driven by object class‐awareness
IET Image Processing, 2021 Current many salient object detection (SOD) models only focus on highlighting visual conspicuous region but fail to make saliency detection for specific targets. In this paper, a selective focus saliency model driven by object class‐awareness (SF‐OCA) to
Danpei Zhao +3 more
doaj +1 more source
The dual nature of TDC – bridging dendritic and T cells in immunity
FEBS Letters, EarlyView.TDC are hematopoietic cells combining dendritic and T cell features. They reach secondary lymphoid organs (SLOs) and peripheral organs (liver and lungs) after FLT3‐dependent development in the bone marrow and maturation in the thymus. TDC are activated and enriched in SLOs upon viral infection, suggesting that they might play unique immune roles, since
Maria Nelli, Mirela Kuka
wiley +1 more source
Cubic convolution interpolation for digital image processing
, 1981 Cubic convolution interpolation is a new technique for resampling discrete data. It has a number of desirable features which make it useful for image processing. The technique can be performed efficiently on a digital computer.
R. Keys
semanticscholar +1 more source
, 2007 The field of image processing addresses handling and analysis of images for many purposes using a large number of techniques and methods. The applications of image processing range from enhancement of the visibility of cer- tain organs in medical images to object recognition for handling by industrial robots and face recognition for identification at ...
van der Heijden, Ferdi, Spreeuwers, Luuk
openaire +1 more source