Rubik’s Cube Due to the annotation of 3D medical data being hard to acquire, the number of annotated 3D images for training is often not enough. Self-supervised learning deeply exploiting the information of raw data can be a solution to…
Data Imbalance Data-Leveling is used when your training data is imbalanced. Methods Upsample: This is where you add new instance for the minority class to balance the data. Downsample: This is where you delete data from the majority class to…
These are the podcasts that are helping me learn AI. 1. “AI Today” by Cognilytica 2. “Super Data Science” by John Krohn 3. “Data Skeptic” by Kyle Polich 4. “Practical AI” by Changelog Media
KL Divergence KL Divergence measures the distance between probability distributions. This is used in various places such as the cross-entropy loss or as a loss function in VAE where you want to constrain the latent distribution to a standard distribution.…
These are the online courses that helped me get a job as an AI engineer from a residential architect. Udemy Machine Learning A-Z™: Hands-On Python & R In Data Science Artificial Intelligence A-Z™: Learn How To Build An AI Deep…
PVTv2 The previous PVT had mainly 3 limitations. When processing high-resolution images, the computational cost is still relatively high. Loses local continuity of the image because it treats the image as a sequence of non-overlapping patches. Inflexible for arbitrary image…
DETR Modern object detectors predict a set of bounding boxes and category labels for each object of interest by defining surrogate regression and classification problems on a large set of proposals. This means that their performances heavily rely on post-processing…
Background When using Traditional CNN-backboned architecture models, due to the convolutional filter’s weights being fully fixed after training, they suffered to adapt to different inputs dynamically. Vision Transformers attempted to remove the convolution from the backbone, but since it is…
Compared with 2D Object Detection, there are several additional parameters to consider when it comes to 3D object detection 2D Object Detection: X coordinate for the center of the bounding box Y coordinate for the center of the bounding box…
I’d like to share 2 different ways to save and load a model using Pytorch. Saving The Entire Model #save model torch.save(model, PATH) #load model model = torch.load(PATH) model.eval() This save/load process has the least amount of code to implement.…