References

1. ImageNet dataset: https://image-net.org/
2. CIFAR-10 dataset: https://www.cs.toronto.edu/~kriz/cifar.html
3. PyTorch vision models: https://pytorch.org/vision/stable/models.html
4. Mastering PyTorch GitHub notebook link to fine-tune AlexNet: https://github.com/arj7192/MasteringPyTorchV2/blob/main/Chapter02/transfer_learning_alexnet.ipynb
5. Hymenoptera dataset (Kaggle link): https://www.kaggle.com/datasets/ajayrana/hymenoptera-data
6. Hymenoptera Genome Database: https://hymenoptera.elsiklab.missouri.edu/
7. Mastering PyTorch GitHub notebook link to run VGG model inference: https://github.com/arj7192/MasteringPyTorchV2/blob/main/Chapter02/vgg13_pretrained_run_inference.ipynb
8. ImageNet class IDs to labels: https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a
9. PyTorch MobileNetV2: https://pytorch.org/hub/pytorch_vision_mobilenet_v2/
10. Capsule neural network: https://en.wikipedia.org/wiki/Capsule_neural_network
11. Region-based convolutional neural networks: https://en.wikipedia.org/wiki/Region_Based_Convolutional_Neural_Networks
12. Object detection, instance segmentation, and person keypoint detection TorchVision models: https://pytorch.org/vision/stable/models.html#object-detection-instance-segmentation-and-person-keypoint-detection

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