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CHINACCS INFORMATION IND CO LTD

Overview
  • Total Patents
    12
  • GoodIP Patent Rank
    138,860
About

CHINACCS INFORMATION IND CO LTD has a total of 12 patent applications. Its first patent ever was published in 2015. It filed its patents most often in China. Its main competitors in its focus markets computer technology, digital networks and it methods for management are CHINA COMSERVICE PUBLIC INFORMATION IND CO LTD, STATE GRID SHANDONG ELECTRIC POWER CO RIZHAO POWER and AURETINA PATENT MANAGEMENT.

Patent filings in countries

World map showing CHINACCS INFORMATION IND CO LTDs patent filings in countries
# Country Total Patents
#1 China 12

Patent filings per year

Chart showing CHINACCS INFORMATION IND CO LTDs patent filings per year from 1900 to 2020

Top inventors

# Name Total Patents
#1 Shu Hongxin 8
#2 Wang Aihua 7
#3 Cai Xiaodong 7
#4 Gao Fengli 2
#5 Liang Xiaoxi 2
#6 Li Longze 2
#7 Wang Xiuying 2
#8 Cheng Tao 2
#9 Asimu Abulizi 1
#10 Chen Jun 1

Latest patents

Publication Filing date Title
CN106557579A A kind of vehicle model searching system and method based on convolutional neural networks
CN106776833A Data of information system exchange method and system of the client to client
CN106778526A A kind of extensive efficient face identification method based on Hamming distance
CN106548165A A kind of face identification method of the convolutional neural networks weighted based on image block
CN106528850A Door access data abnormal detection method based on machine learning clustering algorithm
CN106548164A The relevance recognition methods of facial image and mobile device
CN106776834A A kind of data analysis based on index is from access method and system
CN106326772A Storage method of legal document in web system
CN105678231A Pedestrian image detection method based on sparse coding and neural network
CN105678232A Face image feature extraction and comparison method based on deep learning
CN105631415A Video pedestrian recognition method based on convolution neural network
CN105631413A Cross-scene pedestrian searching method based on depth learning