Convolutional Neural Networks (CNNs) is the most popular neural network model being used for image classification problem. The big idea behind CNNs is that a local understanding of an image is good enough

Top 5 Classification Algorithms in Machine Learning

• Logistic Regression.
• Naive Bayes Classifier.
• K-Nearest Neighbors.
• Decision Tree. Random Forest.
• Support Vector Machines.

Dear Mohsen Ahmadkhani ,

Look the att. file, maybe useful.

Regards,

Shafagat

Shafagat Mahmudova this paper was helpful, thank you.

Convolutional Neural Networks (CNNs) is the most popular neural network model being used for image classification problem. The big idea behind CNNs is that a local understanding of an image is good enough

Top 5 Classification Algorithms in Machine Learning

• Logistic Regression.
• Naive Bayes Classifier.
• K-Nearest Neighbors.
• Decision Tree. Random Forest.
• Support Vector Machines.

Kamal M Alsaad My only concern about the NN-based approaches is their computational cost. Even though they might work well, they are too slow when it comes to a big number of images.

But Thank you for your answer. I should look at them in detail, specially SVM and KNN.

Dear Mohsen Ahmadkhani ,

I agree with Kamal M Alsaad ; I understand your concern about the computational cost of NN/CNN approaches, but you can tackle the training process by using only parts (slices) from the original images. If you are interested in CNN, Pytorch and Tensorflow already have some functions to peforme this process; they also include some models ready to be trained.

If you are programming in python, I'll be glad to give you some tips and ideas to guide you.

Conference Paper Grape Bunch Detection Using A Pixel-Wise Classification In I...

The simplest is Bayesian classification framework via Maximum Likelihood Estimation or Expectation Maximization technique.

Try siamese neural networks

there are a lot of classifiers such as CNN, SVM, Decision Trees, AdaBoost, and KNN. CNN is the best.