Titlebook: Computer Vision, Imaging and Computer Graphics Theory and Applications; 15th International J Kadi Bouatouch,A. Augusto de Sousa,Jose Braz C

不同

書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications影響因子(影響力)




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications被引頻次




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications年度引用




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications年度引用學(xué)科排名




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications讀者反饋




書(shū)目名稱(chēng)Computer Vision, Imaging and Computer Graphics Theory and Applications讀者反饋學(xué)科排名

Priapism

Onerous

JOT

公社

glacial

Scene Text Localization Using Lightweight Convolutional Networksing the fusion of two lightweight neural network architectures, MobileNetV2 and Single Shot Detector (SSD), into our approach named MobText. As experimental results in the ICDAR’11 and ICDAR’13 datasets demonstrates that our solution yields the best trade-off between effectiveness and efficiency in

glacial

Early Stopping for Two-Stream Fusion Applied to Action Recognitionual networks. In addition to reducing overfitting, this method also reduces the training cost, since it usually requires fewer epochs to complete the classification process. Experiments are conducted on UCF101 and HMDB51 datasets, which are two challenging benchmarks in the context of action recogni

脾氣暴躁的人

哎呦

https://doi.org/10.1057/9781137325129rning to automatically construct projections from the extracted features. We show that our three variations of deep learning, which jointly treat feature extraction, selection, and projection, allow efficient creation of high-quality visual overviews of large shape collections, require minimal user

Gum-Disease

https://doi.org/10.1057/9781403983213 humanities may improve and support the daily workflows of humanists. Despite the generally low level of digitization, multiple projects already build a basis to help in digitizing the field. As an example, the . project collected a vast amount of musicological data throughout the last 16 years and