Questions tagged [semantic-segmentation]

Question 1

I'm reading the UNETR paper ("UNETR: Transformers for 3D Medical Image Segmentation") and I'm confused about the training and evaluation methodology for the brain tumor segmentation task on ...

Question 2

I am trying to replicate the paper "UNETR: Transformers for 3D Medical Image Segmentation". In the Implementation Details section, they wrote: In addition, we used data augmentation ...

Question 3

I have a Mask2Former model fine-tuned on my own custom dataset and it is working nicely. I want to play around with knowledge distillation and use my pretrained ...

Question 4

I am using a the segmentation models library and used a UNET model with efficientnet-b7 backbone pretrained on imagenet, to segment immunohistochemistry images.I used augmentations to increase the ...

Question 5

I am working on a medical semantic segmentation problem, where the input is of size (1,256,256) and I have two outputs associated with that input ( two masks ) each with shape ( 1,256,256). For every ...

Question 6

I am currently tackling a semantic segmentation problem where, for each sample, my goal is to segment two masks corresponding to two objects. Notably, object two is typically located inside object one,...

Question 7

In CNNs, I understand how convolution works and how it gradually reduces spatial resolution but increases the channel dimension. E.g. an RGB image of 100x100x3 after a few convolution layers may ...

Question 8

I have a simple UNet model (~1M params) written in Keras 3.0.1, running with a torch backend. My CUDA version is ...

Question 9

I trying to replicate the semantic segmentation example https://keras.io/examples/vision/oxford_pets_image_segmentation/ but train on my own data. I have 8 labels (7 features + background). My images ...

Question 10

I am building a denoising autoencoder to repaint lanes from a binary image. The input is a binary image that has incomplete lanes, due to vehicles getting in the way. I repaint the lanes manually so ...

Question 11

I'm training Unet+MobileNetV3 for semantic segmentation objects on real photos using custom dataset and get strange results. I have already accumulated pretty big dataset and constantly improve it by ...

Question 12

I have a set of 120x120 input images with 3 channels. I want to build a basic CNN to predict the value of each pixel. I have 2 doubts. One is regarding the last layer - should be a Dense layer, or a ...

Question 13

Current object detection architectures like Faster-RCNN and YOLO seem to be overcomplicated in comparsion with segmentation architectures like Unet. So, why can't we just draw some rectangles around ...

Question 14

I have been trying to use MaskRCNN with a Resnet backbone on the DeepFashion2 Dataset for instance segmentation. The custom configurations are as follows: ...

Question 15

I'm interested in finding an embedding vector for each segment found by the Facebook/Meta Segment Anything model (for classification and tracking of segments). Can ...

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Questions tagged [semantic-segmentation]

UNETR paper — Does brain tumor segmentation use 5-fold CV or 80:15:5 split?

Clarification on “random scale” in UNETR data augmentation

How to correctly implement the loss function for my distillation of Mask2Former?

decreased prediction accuracy of segmentation model on using smaller size but higher resolution images

Am I following the correct approach?

Per Channel loss or Per Sample Loss

How do transposed convolutions in CNNs reduce the channel dimensionality?

Why can't I increase my GPU utilization?

How do I ensure final output shape matches input shape for a semantic segmentation task?

Trying to train a denoising autoencoder to restore missing information from a binary image

Semantic segmentation sometimes give bad result

Building a CNN (with Keras for pixelwise classification)

Why not using segmentation architectures for object detection?

MaskRCNN.train gives 'list index out of range'

Meta's SAM model: can extract semantic embedding vector?

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