Results 21 to 30 of about 3,652,577 (286)
Image Super-Resolution Using Deep Convolutional Networks [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014 We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images.
Chao Dong +3 more
semanticscholar +1 more source
Fluorescent sensors for imaging of interstitial calcium
Nature Communications, 2023 Calcium in interstitial fluids is central to systemic physiology and a crucial ion pool for entry into cells through numerous plasma membrane channels. Its study has been limited by the scarcity of methods that allow monitoring in tight inter-cell spaces
Ariel A. Valiente-Gabioud +8 more
doaj +1 more source
Cell Reports, 2023 Summary: Most gastrointestinal stromal tumors (GISTs) develop due to gain-of-function mutations in the tyrosine kinase gene, KIT. We recently showed that mutant KIT mislocalizes to the Golgi area and initiates uncontrolled signaling.
Yuuki Obata +8 more
doaj +1 more source
Efficient Long-Range Attention Network for Image Super-resolution [PDF]
European Conference on Computer Vision, 2022 Recently, transformer-based methods have demonstrated impressive results in various vision tasks, including image super-resolution (SR), by exploiting the self-attention (SA) for feature extraction.
Xindong Zhang +3 more
semanticscholar +1 more source
IMPACT OF DEEP LEARNING-BASED SUPER-RESOLUTION ON BUILDING FOOTPRINT EXTRACTION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Automated building footprints extraction from High Spatial Resolution (HSR) remote sensing images plays important roles in urban planning and management, and hazard and disease control. However, HSR images are not always available in practice.
H. He +9 more
doaj +1 more source
Multiple Frame Splicing and Degradation Learning for Hyperspectral Imagery Super-Resolution
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral imagery (HSI) is an emerging remote sensing technology to discriminate different remote sensing objects. However, the HSI spatial resolution is relatively low due to the trade-off in restricted physical hardware and various imaging ...
Chenwei Deng, Xingshi Luo, Wenzheng Wang
doaj +1 more source
Accurate Image Super-Resolution Using Very Deep Convolutional Networks [PDF]
Computer Vision and Pattern Recognition, 2015 We present a highly accurate single-image superresolution (SR) method. Our method uses a very deep convolutional network inspired by VGG-net used for ImageNet classification [19].
Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee
semanticscholar +1 more source
Disentangling Light Fields for Super-Resolution and Disparity Estimation [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Light field (LF) cameras record both intensity and directions of light rays, and encode 3D cues into 4D LF images. Recently, many convolutional neural networks (CNNs) have been proposed for various LF image processing tasks.
Yingqian Wang +6 more
semanticscholar +1 more source
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment [PDF]
Computer Vision and Pattern Recognition, 2021 A recurrent structure is a popular framework choice for the task of video super-resolution. The state-of-the-art method BasicVSR adopts bidirectional propagation with feature alignment to effectively exploit information from the entire input video.
Kelvin C. K. Chan +3 more
semanticscholar +1 more source
Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks [PDF]
, 2018 Enhancing resolution is a permanent goal in magnetic resonance (MR) imaging, in order to keep improving diagnostic capability and registration methods.
Domínguez-Merino, Enrique +4 more
core +1 more source