Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Wild animal optimization identification algorithm based on convolutional neural network

A convolutional neural network and wild animal technology, applied in biological neural network models, neural architectures, animal repellants, etc., can solve problems such as incomplete data, low recognition rate, slow data reception and transmission, and achieve safe use Convenient, scientific and reasonable structure

Pending Publication Date: 2020-10-30
江苏叁拾柒号仓智能科技有限公司
View PDF0 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides an optimized identification algorithm for wild animals based on convolutional neural network, which can effectively solve the problem that the optimized identification algorithm for wild animals on the market is not comprehensive enough, slow in data reception and transmission, and cannot Statistical and analysis of data, resulting in low recognition rate and incomplete information

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Wild animal optimization identification algorithm based on convolutional neural network
  • Wild animal optimization identification algorithm based on convolutional neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0030] Example: such as Figure 1-2 As shown, the present invention provides a technical solution, a recognition algorithm based on convolutional neural network optimization for wild animals, including a calculation module, a transmission module, a positioning module and a recognition module;

[0031] The calculation module is used for data calculation;

[0032] The transmission module is used for high-speed and low-latency transmission;

[0033] The positioning module is used for satellite positioning to form position positioning;

[0034] The recognition module is used for bird voiceprint recognition.

[0035] According to the above technical solution, the calculation module relies on the high-computing GPU computing power cloud, and the deep learning algorithm model built through the 150-layer convolutional neural network architecture can accurately identify tiny wild animals. The joint development with Bitmain chips can be deployed in their cluster environment and edge ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a wild animal optimization identification algorithm based on a convolutional neural network. A calculation module, a transmission module, a positioning module and an identification module are included. The calculation module is used for calculating data; the transmission module is used for high-speed low-delay transmission; the positioning module is used for satellite positioning to form positioning; the identification module is used for bird voiceprint recognition. The structure is scientific and reasonable, the algorithm is safe and convenient to use, the calculationmodule is used for calculating data; the transmission module is used for high-speed low-delay transmission; the positioning module is used for satellite positioning and forming the positioning, and the identification module is used for bird voiceprint recognition, so that the accurate monitoring of wild animals is completed together, air, space and ground data are output on an integrated platform,the analysis data of most national protection areas and wild protection institutions finally form data statistics and analysis of national main wild animals, and the variation trend of species is monitored in real time.

Description

technical field [0001] The invention relates to the technical field of wild animal optimization recognition, in particular to a convolutional neural network-based recognition algorithm for wild animal optimization. Background technique [0002] Wild animals refer to animals that grow in the natural environment and have not been domesticated. Wild animals can be divided into broad and narrow senses. In a broad sense, they generally refer to beasts, birds, reptiles, amphibians, fish, molluscs and insects. In a narrow sense, it refers to the above-mentioned types of animals except fish and invertebrates, including beasts, birds, reptiles and amphibians. According to the close relationship between wild animals and humans, wild animals can be divided into wild animals. Wild animals in the environment and artificially bred wild animals, the wild animals protected under the "Wild Animal Protection Law" refer to precious and endangered terrestrial and aquatic wild animals and terres...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G10L17/26G06N3/04A01M29/10H04L29/06
CPCG10L17/26A01M29/10H04L63/0227H04L63/0428H04L67/01G06N3/045
Inventor 卞石磊
Owner 江苏叁拾柒号仓智能科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products