Table 2 Separate evaluation of each static and dynamic sign using the proposed method.

From: Exploiting domain transformation and deep learning for hand gesture recognition using a low-cost dataglove

Static gestures

Dynamic gestures

Gesture

Precision

Recall

F1-score

Gesture

Precision

Recall

F1-score

a

0.8429

0.88

0.8611

Bad

1

0.996

0.998

b

1

0.996

0.998

Deaf

1

0.988

0.994

c

0.638

0.564

0.5987

Fine

0.9839

0.976

0.9799

d

0.7749

0.84

0.8061

Good

0.988

0.992

0.99

e

0.5611

0.716

0.6292

Goodbye

0.996

0.992

0.994

f

0.996

1

0.998

Hello

0.9655

0.896

0.9295

g

1

1

1

Hungry

1

0.976

0.9879

h

0.9843

1

0.9921

j

0.9798

0.968

0.9738

i

0.9368

0.948

0.9423

Me

1

0.96

0.9796

k

0.8042

0.772

0.7878

No

0.9553

0.94

0.9476

l

0.9144

0.94

0.927

Please

1

1

1

m

0.9424

0.916

0.929

Sorry

0.9286

0.988

0.9574

n

0.9102

0.932

0.9209

Thankyou

0.9484

0.956

0.9522

o

0.6518

0.644

0.6479

Yes

0.9234

0.964

0.9432

p

0.8301

0.86

0.8448

You

0.9843

1

0.9921

q

0.949

0.968

0.9584

    

s

0.4639

0.36

0.4054

    

t

0.7389

0.6

0.6623

    

u

0.59

0.616

0.6027

    

v

0.6224

0.6

0.611

    

w

1

1

1

    

x

0.7724

0.828

0.7992

    

y

0.9035

0.936

0.9194

    

z

0.9318

0.984

0.9572

    
Back to article page