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  • deep learning - What is Panoptic Segmentation? - Artificial . . .
    In computer vision what is Panoptic Segmentation about? How it relates to Semantic Segmentation? and how it compares to Instance Segmentation?
  • What are the practical differences between Panoptic Segmentation and . . .
    Do panoptic segmentation models internally combine semantic + instance segmentation, or do they treat these tasks differently? Are there any real-world applications (autonomous driving, robotics, medical imaging, etc ) where the choice between the two architectures meaningfully changes performance or system behavior?
  • Recently Active instance-segmentation Questions - Artificial . . .
    For questions about instance segmentation, which is the task of detecting and delineating each distinct object of interest appearing in an image (even the ones belong to the same class) Instance segmentation is different from semantic segmentation, where objects that belong to the same class are not differentiated Collectively, instance and semantic segmentation fall into the category of
  • What are the practical differences between panoptic segmentation and . . .
    While reading computer vision papers and tutorials, I often see panoptic segmentation and instance segmentation described together However, it’s still unclear how they differ in practice: What pr
  • training - Is batch size of 1 a valid choice for a very deep neural . . .
    I am training a very deep neural network (Panoptic-DeepLab) with a ResNet34 backbone on Google Colab on CityScapes dataset for Panoptic Segmentation, and noticed that, with a big crop size, the batch size has to be decreased to 1 image per batch, otherwise CUDA out of memory issues start to occur
  • Which evaluation methods can I use for image segmentation?
    The paper referenced by Martin Thoma is the go-to for semantic segmentation However I will also like to add the Panoptic Segmentation metric as an aggregated method to measure both the detection task and segmentation task of the model It is a very well-known and widely used metric since it is the standard metric for COCO dataset (segmentation) This is the paper where the metric is proposed
  • How can I deal with images of variable dimensions when doing image . . .
    However, in my case, I cannot crop the image and keep its center or something similar, since, in segmentation, I want the output to be of the same dimensions as the input This paper suggests that in a segmentation task one can feed the same image multiple times to the network but with a different scale and then aggregate the results
  • Vision transformer for image segmentation - Artificial Intelligence . . .
    1 I am working with vision transformers (ViT) for the task of image segmentation, but I am unsure of which segmentation head to use I know I need a vision transformer as my backbone, and a segmentation head to generate the image segmentation from the learned representations of the backbone given an input image
  • machine learning - What is a fully convolution network? - Artificial . . .
    An example of a fully convolutional network is the U-net (called in this way because of its U shape, which you can see from the illustration below), which is a famous network that is used for semantic segmentation, i e classify pixels of an image so that pixels that belong to the same class (e g a person) are associated with the same label (i
  • python - Langchain agent state preservation - Artificial Intelligence . . .
    I've been trying to create my first agent using Langchain I would like some way to store user details, what questions they may be asking etc to be able to effectively govern how the LLM responds





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