DDistill-SR: Reparameterized dynamic distillation network for lightweight image super-resolution
Recent research on deep convolutional neural networks (CNNs) has provided a significant
performance boost on efficient super-resolution (SR) tasks by trading off the performance …
performance boost on efficient super-resolution (SR) tasks by trading off the performance …
Image scaling by de la vallée-poussin filtered interpolation
We present a new image scaling method both for downscaling and upscaling, running with
any scale factor or desired size. The resized image is achieved by sampling a bivariate …
any scale factor or desired size. The resized image is achieved by sampling a bivariate …
Efficient neural image decoding via fixed-point inference
Recent learned image coding has emerged with superior efficiency to conventional
methods. It, however, is criticized for its complexity-exhaustive deep neural network (DNN) …
methods. It, however, is criticized for its complexity-exhaustive deep neural network (DNN) …
The impact of black edge artifact on qoe of the fov-based cloud vr services
Cloud virtual reality (Cloud VR) services usually introduce high latency in rendering and
streaming, resulting in a mismatch between the visual and vestibular systems, causing user …
streaming, resulting in a mismatch between the visual and vestibular systems, causing user …
Efficient GPU Cloud architectures for outsourcing high-performance processing to the Cloud
The world is becoming increasingly dependant in computing intensive applications. The
appearance of new paradigms, such as Internet of Things (IoT), and advances in …
appearance of new paradigms, such as Internet of Things (IoT), and advances in …
Decoder-side cross resolution synthesis for video compression enhancement
This paper proposes a decoder-side Cross Resolution Synthesis (CRS) module to pursue
better compression efficiency beyond the latest Versatile Video Coding (VVC), where we …
better compression efficiency beyond the latest Versatile Video Coding (VVC), where we …
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 …
[HTML][HTML] An Open Image Resizing Framework for Remote Sensing Applications and Beyond
Image resizing (IR) has a crucial role in remote sensing (RS), since an image's level of detail
depends on the spatial resolution of the acquisition sensor; its design limitations; and other …
depends on the spatial resolution of the acquisition sensor; its design limitations; and other …
H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System
High-speed, high-resolution stereoscopic (H2-Stereo) video allows us to perceive dynamic
3D content at fine granularity. The acquisition of H2-Stereo video, however, remains …
3D content at fine granularity. The acquisition of H2-Stereo video, however, remains …
[图书][B] Artificial intelligence applications for health care
This book takes an interdisciplinary approach covering health care, cognitive computing,
and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and …
and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and …