Edge-oriented convolution block for real-time super resolution on mobile devices
Efficient and light-weight super resolution (SR) is highly demanded in practical applications.
However, most of the existing studies focusing on reducing the number of model parameters …
However, most of the existing studies focusing on reducing the number of model parameters …
A deep learning based medical image segmentation technique in Internet-of-Medical-Things domain
Abstract Medical Image Segmentation is the process of automatic or semi-automatic
detection of boundaries within a 2D or 3D image in Internet-of-Medical-Things (IoMT) …
detection of boundaries within a 2D or 3D image in Internet-of-Medical-Things (IoMT) …
Optimal deep learning based convolution neural network for digital forensics face sketch synthesis in internet of things (IoT)
The rapid development in 5G cellular and IoT technologies is expected to be deployed
widespread in the next few years. At the same time, crime rates are also increasing to a …
widespread in the next few years. At the same time, crime rates are also increasing to a …
RADC-Net: A residual attention based convolution network for aerial scene classification
With rapid development of satellite and airplane platforms, aerial image has become more
and more accessible. Aerial image scene classification plays an important role in many …
and more accessible. Aerial image scene classification plays an important role in many …
Wavelet-based residual attention network for image super-resolution
S Xue, W Qiu, F Liu, X ** - Neurocomputing, 2020 - Elsevier
Image super-resolution (SR) is a fundamental technique in the field of image processing and
computer vision. Recently, deep learning has witnessed remarkable progress in many super …
computer vision. Recently, deep learning has witnessed remarkable progress in many super …
Fourier transform profilometry using single-pixel detection based on two-dimensional discrete cosine transform
T Li, Y Dong, X Wang - Optics & Laser Technology, 2022 - Elsevier
We present a single-pixel Fourier transform profilometry (FTP) for obtaining three-
dimensional (3D) maps with few measurements. Two digital micromirror devices were …
dimensional (3D) maps with few measurements. Two digital micromirror devices were …
Ghostsr: Learning ghost features for efficient image super-resolution
Modern single image super-resolution (SISR) system based on convolutional neural
networks (CNNs) achieves fancy performance while requires huge computational costs. The …
networks (CNNs) achieves fancy performance while requires huge computational costs. The …
Fast-Vid2Vid++: Spatial-Temporal Distillation for Real-Time Video-to-Video Synthesis
Video-to-Video synthesis (Vid2Vid) gains remarkable performance in generating a photo-
realistic video from a sequence of semantic maps, such as segmentation, sketch and pose …
realistic video from a sequence of semantic maps, such as segmentation, sketch and pose …
[PDF][PDF] Evaluation of scratch and pre-trained convolutional neural networks for the classification of Tomato plant diseases
Plant diseases are a major cause of destruction and death of most plants and especially
trees. However, with the help of early detection, this issue can be solved and treated …
trees. However, with the help of early detection, this issue can be solved and treated …
MRI image synthesis with dual discriminator adversarial learning and difficulty-aware attention mechanism for hippocampal subfields segmentation
Background and objective Hippocampal subfields (HS) segmentation accuracy on high
resolution (HR) MRI images is higher than that on low resolution (LR) MRI images. However …
resolution (HR) MRI images is higher than that on low resolution (LR) MRI images. However …