On a four-species African wildlife dataset, ViT-H/14 reaches 99% accuracy versus 67% for the best CNN (DenseNet-201), but at far greater computational cost.
Advancements in Image Classification using Convolutional Neural Network
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Convolutional Neural Network (CNN) is the state-of-the-art for image classification task. Here we have briefly discussed different components of CNN. In this paper, We have explained different CNN architectures for image classification. Through this paper, we have shown advancements in CNN from LeNet-5 to latest SENet model. We have discussed the model description and training details of each model. We have also drawn a comparison among those models.
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Evaluating Deep Learning Models for African Wildlife Image Classification: From DenseNet to Vision Transformers
On a four-species African wildlife dataset, ViT-H/14 reaches 99% accuracy versus 67% for the best CNN (DenseNet-201), but at far greater computational cost.