Titlebook: Neural Information Processing; 19th International C Tingwen Huang,Zhigang Zeng,Chi Sing Leung Conference proceedings 2012 Springer-Verlag B

不服從

書目名稱Neural Information Processing影響因子(影響力)




書目名稱Neural Information Processing影響因子(影響力)學(xué)科排名




書目名稱Neural Information Processing網(wǎng)絡(luò)公開度




書目名稱Neural Information Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Neural Information Processing被引頻次




書目名稱Neural Information Processing被引頻次學(xué)科排名




書目名稱Neural Information Processing年度引用




書目名稱Neural Information Processing年度引用學(xué)科排名




書目名稱Neural Information Processing讀者反饋




書目名稱Neural Information Processing讀者反饋學(xué)科排名

高興一回

0302-9743 containing articles on theoretical analysis, neural modeling, algorithms, applications, as well as simulation and synthesis.978-3-642-34477-0978-3-642-34478-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

缺陷

Optimization of a Neural Network for Computer Vision Based Fall Detection with Fixed-Point Arithmetihave a major impact on the run-time performance of the neural network. In summary, we achieved a speedup of 48 for multiplication, 39.5 for additions, and 194 for the transfer functions and, thus, realized an embedded real-time fall detection system.

骨

Estimation of Missing Precipitation Records Using Modular Artificial Neural Networksfrom both networks. The experimental results showed that modular artificial neural networks provided a higher accuracy than single artificial neural network and other conventional methods in terms of mean absolute error.

經(jīng)典

Classification of Interview Sheets Using Self-Organizing Maps for Determination of Ophthalmic Examint to be checked is given as the label of the winner neuron for the presented data. It is established that the proposed method achieves as favorable classification accuracy as initial determination made by ophthalmologists.

腐敗

高談闊論

傀儡

擦掉

PEAQ Compatible Audio Quality Estimation Using Computational Auditory Modelred to the PEAQ advanced version, the proposed estimation system has a considerable improvement in performance both in terms of the correlation and MSE (Mean Square Error). By combining the computational auditory model and PEAQ, our estimation system can be applied to the quality assessment of highly impaired audio.

改革運(yùn)動(dòng)

A System for Offline Character Recognition Using Auto-encoder Networksease the classification performance further. We observe 94.25% accuracy for the two hidden layer network on Consonant data and 94.1% on Vowel Modifier Dataset which increases to 95.4% for Consonant and 94.8% for Vowel Modifier Dataset after combining classifiers to form an ensemble classifier of 4 different two hidden layer networks.