Titlebook: Digital Multimedia Communications; 19th International F Guangtao Zhai,Jun Zhou,Jia Wang Conference proceedings 2023 The Editor(s) (if appli

Intermediary

書目名稱Digital Multimedia Communications影響因子(影響力)




書目名稱Digital Multimedia Communications影響因子(影響力)學(xué)科排名




書目名稱Digital Multimedia Communications網(wǎng)絡(luò)公開度




書目名稱Digital Multimedia Communications網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Digital Multimedia Communications被引頻次




書目名稱Digital Multimedia Communications被引頻次學(xué)科排名




書目名稱Digital Multimedia Communications年度引用




書目名稱Digital Multimedia Communications年度引用學(xué)科排名




書目名稱Digital Multimedia Communications讀者反饋




書目名稱Digital Multimedia Communications讀者反饋學(xué)科排名

勤勉

1865-0929 nized in topical sections as follows: Computer Vision; Image Analysis; Quality Assessment; Video Processing; Machine Learning; and Big data..978-981-99-0855-4978-981-99-0856-1Series ISSN 1865-0929 Series E-ISSN 1865-0937

BLINK

coagulate

Parameters, Scales and Geostrophic Balance and the CNN structure can provide additional local information to the transformer. The fusion of global information and local information is conducive to the second transfer encoder to make better decisions. Experiments results on large-size dataset for industrial smoke detection illustrate the effectiveness of the proposed model.

脆弱帶來

違抗

John Vince MTech, PhD, DSc, CEng, FBCSmage. Then we design a novel Kernel Fast Fourier Convolution (KFFC) to filter the image feature of the transitional image with the raw blur kernel in the frequency domain. Extensive experiments show that our methods achieve favorable and robust results.

違抗

Errata,hts of features at different scales. We conduct extensive experiments on Hubei water dataset we constructed, The results show the framework effectively improves the accuracy of water segmentation and greatly improves the visual effect of segmentation, which is 5.9% higher in self-made dataset with advanced methods.

周年紀(jì)念日

Pedestrian Re-recognition Based on?Memory Network and?Graph Structuresults shows that the Rank 1 of the GCPRN network on iLIDS Video re-identification (iLIDS-VID) dataset reaches . and Rank 5 reached ., surpassing the Unsupervised Tracklet Association Learning (UTAL) and Temporal Knowledge Propagation (TKP) algorithm that reached a high level on the iLIDS-VID dataset.

conifer

SYN

Feature Adaptation Predictive Coding for Quantized Block Compressive Sensing of COVID-19 X-Ray Imageet. The proposed method can implement the high-efficiency encoding of X-ray images, and then swiftly transmit the telemedicine-oriented chest images. The experimental results show that compared with the state-of-the-art predictive coding methods, both rate-distortion and complexity performance of our FAPC method have enough competitive advantages.