ResViT: residual vision transformers for multimodal medical image synthesis
Generative adversarial models with convolutional neural network (CNN) backbones have
recently been established as state-of-the-art in numerous medical image synthesis tasks …
recently been established as state-of-the-art in numerous medical image synthesis tasks …
Haar wavelet downsampling: A simple but effective downsampling module for semantic segmentation
Downsampling operations such as max pooling or strided convolution are ubiquitously
utilized in Convolutional Neural Networks (CNNs) to aggregate local features, enlarge …
utilized in Convolutional Neural Networks (CNNs) to aggregate local features, enlarge …
I2I-Mamba: Multi-modal medical image synthesis via selective state space modeling
In recent years, deep learning models comprising transformer components have pushed the
performance envelope in medical image synthesis tasks. Contrary to convolutional neural …
performance envelope in medical image synthesis tasks. Contrary to convolutional neural …
Image downscaling via co-occurrence learning
Image downscaling is one of the widely used operations in image processing and computer
graphics. It was recently demonstrated in the literature that kernel-based convolutional filters …
graphics. It was recently demonstrated in the literature that kernel-based convolutional filters …
Learned fractional downsampling network for adaptive video streaming
Given increasing demand for very large format contents and displays, spatial resolution
changes have become an important part of video streaming. In particular, video downscaling …
changes have become an important part of video streaming. In particular, video downscaling …
Nonlocal co-occurrence for image downscaling
Image downscaling is one of the widely used operations in image processing and computer
graphics. It was recently demonstrated in the literature that kernel-based convolutional filters …
graphics. It was recently demonstrated in the literature that kernel-based convolutional filters …
Improving Netflix video quality with neural networks
Video downscaling is an important component of adaptive video streaming, which tailors
streaming to screen resolutions of different devices and optimizes picture quality under …
streaming to screen resolutions of different devices and optimizes picture quality under …
[PDF][PDF] Novel deep learning algorithms for multi-modal medical image synthesis
O Dalmaz - 2023 - repository.bilkent.edu.tr
Coklu kip tıbbi görüntüleme, doku morfolojisi ve islevi hakkında tamamlayıcı bilgiler
saglayarak çesitli hastalıkların tanı ve tedavisinde güçlü bir araçtır. Ancak, farklı kip veya …
saglayarak çesitli hastalıkların tanı ve tedavisinde güçlü bir araçtır. Ancak, farklı kip veya …
Fully Convolutional Fractional Scaling
Fully convolutional networks can be applied to any size input but till now do not support non-
integer scaling. We introduce a fully convolutional fractional scaling component, FCFS. Our …
integer scaling. We introduce a fully convolutional fractional scaling component, FCFS. Our …
Codec rate distortion compensating downsampler
A system includes a machine learning (ML) model-based video downsampler configured to
receive an input video sequence having a first display resolution, and to map the input video …
receive an input video sequence having a first display resolution, and to map the input video …