Human palm recognition system using convolutional neural network SQUEEZENET used in law enforcement for mug shot identification, comprises palm recognition application, which can cover wide spectrum from well controlled environment to uncontrolled one
	RANGANAYAKI J; CH A S V; RAVINDRA S; DINESH S; ABHILASH S; KALIYAMURTHIE K P
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069700-A
成果简介	NOVELTY - Human palm recognition system using convolutional neural network (CNN) SQUEEZENET comprises palm recognition application, which can cover a wide spectrum from a well controlled environment to an uncontrolled one, and in a controlled environment, frontal and profile photographs of human faces are taken complete with a uniform background and identical poses among the participants. These palm images are commonly called mug shots. Each mug shot can be manually or automatically cropped to extract a normalized subpart called a canonical palm image. USE - Human palm recognition system using convolutional neural network SQUEEZENET used in law enforcement for mug shot identification, verification for personal identification such as driver's licenses and credit cards, gateways to limited access areas, and surveillance of crowd behavior. ADVANTAGE - The human palm recognition system has minimized size and position of the Palm are normalized approximately to the predefined values and the background region in canonical palm image.
IPC 分类号	A47G-019/22 ; A61K-036/889 ; G06F-003/03 ; G06T-011/60 ; G07C-009/37
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19590
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	RANGANAYAKI J,CH A S V,RAVINDRA S,et al. Human palm recognition system using convolutional neural network SQUEEZENET used in law enforcement for mug shot identification, comprises palm recognition application, which can cover wide spectrum from well controlled environment to uncontrolled one. IN202341069700-A[P]. 2023.

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