Results 211 to 220 of about 87,061 (254)

Can social media videos meet patients' information needs for benign prostatic hyperplasia? A repeated cross-sectional study. [PDF]

BMC Urol
Tian C, Wang W, Tao J, Luo G, Zhou J.
europepmc   +1 more source

Assessment of the consistency between YouTube videos and scientific evidence on paediatric myopia control. [PDF]

PLoS One
Pérez-Mañá L, Ortiz C, Sunyer-Grau B, Alonso S, Argilés M.   +4 more
europepmc   +1 more source

Machine Learning Models for Early Autism Spectrum Disorder Detection: Systematic Review With a Pediatric and Engineering Perspective. [PDF]

Cureus
Onyango C, Wanjiku LN, Oketch C.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

No-reference screen content video quality assessment

Displays, 2021
Abstract How to effectively and accurately measure the degradation of media content is an important research topic in the field of image or video processing. Application scenarios such as online meetings, distance learning, and live game streaming make screen content video become a hot spot in Video Quality Assessment (VQA) research.
Xiongkuo Min, Wenhan Zhu, Wenjun Zhang
exaly   +3 more sources

Predictive no-reference assessment of video quality [PDF]

Signal Processing: Image Communication, 2017
Among the various means to evaluate the quality of video streams, lightweight No-Reference (NR) methods have low computation and may be executed on thin clients. Thus, these methods would be perfect candidates in cases of real-time quality assessment, automated quality control and in adaptive mobile streaming. Yet, existing real-time, NR approaches are
Antonio Liotta, Stavros Stavrou, Decebal Constantin Mocanu   +2 more
exaly   +3 more sources

No-reference video quality assessment in the compressed domain

IEEE Transactions on Consumer Electronics, 2012
In this paper, a novel no-reference video quality assessment algorithm in the compressed domain is introduced. The proposed algorithm takes into account of three key factors; the quantization parameter, the motion, and the bit allocation factor which are calculated using the information extracted from the compressed bitstream.
Xiangyu Lin, Hanjie Ma, Lei Luo, Yaowu Chen   +3 more
exaly   +3 more sources

COME for No-Reference Video Quality Assessment

2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), 2018
Nowadays, the issue of objective Video Quality Assessment (VQA) has been extensively studied. In this paper, we present an effective general-purpose VQA method named COnvolutional neural network and Multi-regression based Evaluation (COME). It requires no referred lossless video and is universal for non-specific types of distortion.
Chunfeng Wang, Li Su 0003, Weigang Zhang
openaire   +2 more sources