MahaPala 2023.12.16

Detection of fruits disease by using Machine learning

MahaPala

Detection of fruits disease by using Machine learning

Indentification Of Fruits

Create class to indentify the fruit names tested it for Guava & Mango fruits

• Deep learning algorithm
• adam optimizer
• relu activation

Reference

• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4245116/

Model: sequential

_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 rescaling (Rescaling)       (None, 224, 224, 3)       0         
                                                                 
 conv2d (Conv2D)             (None, 224, 224, 16)      448       
                                                                 
 max_pooling2d (MaxPooling2  (None, 112, 112, 16)      0         
 D)                                                              
                                                                 
 conv2d_1 (Conv2D)           (None, 112, 112, 32)      4640      
                                                                 
 max_pooling2d_1 (MaxPoolin  (None, 56, 56, 32)        0         
 g2D)                                                            
                                                                 
 conv2d_2 (Conv2D)           (None, 56, 56, 64)        18496     
                                                                 
 max_pooling2d_2 (MaxPoolin  (None, 28, 28, 64)        0         
 g2D)                                                            
                                                                 
 flatten (Flatten)           (None, 50176)             0         
                                                                 
 dense (Dense)               (None, 128)               6422656   
                                                                 
 dense_1 (Dense)             (None, 5)                 645       
                                                                 
=================================================================
Total params: 6446885 (24.59 MB)
Trainable params: 6446885 (24.59 MB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________

Dashboard

Release Note

2023.12.16

• #9 Create a sample to identify the fruits name
• #11 Implement visualization dashboard

2021.11.01

• #9 Create a sample to identify the fruits name

2020.11.01.dev

• Initial setup and environments
• Added a templete matching algorithm