DL-MAML：一种新的蝴蝶物种自动识别模型.pdf

计算机研究与发展DOI：10.7544/issn1000-1239.202220860

Journal

of

Computer

Research

and

Development61（3）：674−684，2024

DL-MAML：一种新的蝴蝶物种自动识别模型

赵戈伟许升全谢娟英121

1

（陕西师范大学计算机科学学院西安710119）

2

（陕西师范大学生命科学学院西安710119）

（zgv@）

DL-MAML：AnInnovativeModelforAutomaticallyIdentifyingButterflySpecies

1

2

1

Zhao

Gewei,

Xu

Shengquan,

and

Xie

Juanying

1

（SchoolofComputerScience,ShaanxiNormalUniversity,Xi’an710119）

2

（CollegeofLifeSciences,ShaanxiNormalUniversity,Xi’an710119）

AbstractThere

are

tens

of

thousands

of

butterfly

species.

Each

butterfly

species

is

closely

related

to

a

specific

type

of

plants.

It

is

significant

to

study

butterfly

species

automatic

identification.

However,

it

is

very

challenging

to

study

butterfly

species

recognition

via

the

images

taken

in

the

field

environments.

One

reason

is

that

there

are

small

number

of

butterfly

species

in

the

existing

datasets

compared

with

the

reported

species

in

the

world.

The

other

reason

is

that

the

number

of

samples

(images)

of

each

butterfly

species

is

limited

in

the

datasets.

These

situations

make

it

challengeable

to

train

a

general

system

for

butterfly

species

identification

via

machine

learning

algorithms.

In

addition,

butterfly

wings

are

always

folded

in

the

images

taken

in

the

field

environments,

which

make

it

challengeable

to

learn

butterfly

classification

features,

which

further

make

it

difficult

to

study

butterfly

species

recognition

using

machine

learning

techniques.

Therefore,

meta-learning

is

introduced

to

address

the

challenges,

and

DL-MAML

(deep

learning

advanced

model-agnostic

meta-learning)

algorithm

is

proposed

for

identi