EMERGING TRENDS IN COMPUTING
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Perceptron
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RNN
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CNN
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Fully connected neural network
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Detailed explanation-1: -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.
Detailed explanation-2: -Conclusion. Thus, in this blog, we discussed how to use image classification in Machine Learning by implementing four common ML algorithms including Random Forest, KNN, Decision Tree, and Naive Bayes classifier. Due to their poor accuracies, Deep learning is preferred for image classification tasks.
Detailed explanation-3: -They are both unique in how they work mathematically, and this causes them to be better at solving specific problems. In general, CNN tends to be a more powerful and accurate way of solving classification problems. ANN is still dominant for problems where datasets are limited, and image inputs are not necessary.
Detailed explanation-4: -Deep Learning Algorithms for Image Processing and Image Classification. Convolutional neural networks (CNNs) are best suited for image processing and image classification problems as the convolution operation allows processing the images with the help of different filter functions.