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- No-reference image quality assessment based on spatial and spectral . . .
We develop an efficient general-purpose no-reference (NR) image quality assessment (IQA) model that utilizes local spatial and spectral entropy featur…
- An End-to-End No-Reference Video Quality Assessment . . . - IEEE Xplore
In this paper, we propose a deep neural network-based no-reference (NR) video quality assessment (VQA) method with spatiotemporal feature fusion and hierarchical information integration to evaluate the perceptual quality of videos First, a feature extraction model is proposed by using 2D and 3D convolutional layers to gradually extract spatiotemporal features from raw video clips Second, we
- CVPR 2024 Open Access Repository
These CVPR 2024 papers are the Open Access versions, provided by the Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore
- No-Reference Image Quality Assessment via Transformers, Relative . . .
Abstract The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the perceptual image quality in ac-cordance with subjective evaluations, it is a complex and unsolved problem due to the absence of the pristine refer-ence image In this paper, we propose a novel model to ad-dress the NR-IQA task by leveraging a hybrid approach that benefits from Convolutional Neural Networks
- CVPR 2022 Open Access Repository
These CVPR 2022 workshop papers are the Open Access versions, provided by the Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore
- Hybrid No-Reference Video Quality Models for H. 264 with Encrypted . . .
The proposed hybrid noreference models uses both the information available from video packets and decoded signals to estimate coding artefacts and impairments caused by transmission errors Sometime, the payloads of video packets may be encrypted to protect contents In such case, the available information is rather limited
- Wood Types, Characteristics and Identification Guide - Wood Assistant
Wood Database - Hardwood and Softwood Identification Guide Wood types are incredibly versatile and diverse, enabling them to be used for many different purposes The data presented here is intended to help you better understand the properties of wood This includes wood characteristics insights, which will enable you to understand better the specific properties of each species of wood, its
- An accurate deep convolutional neural networks model for no-reference . . .
The goal of image quality assessment (IQA) is to use computational models to measure the consistency between image quality and subjective evaluations In recent years, convolutional neural networks (CNNs) have been widely used in image processing community and have achieved performance leaps than non CNNs-based methods In this work, we describe an accurate deep CNNs model for no-reference IQA
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