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Transformation Invariant Cancerous Tissue Classification Using Spatially Transformed DenseNet

arXiv 2204.11066 ↗First posted 23 Apr 2022eess.IV cs.CV cs.LGcited by 0

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Abstract (arXiv)

In this work, we introduce a spatially transformed DenseNet architecture for transformation invariant classification of cancer tissue. Our architecture increases the accuracy of the base DenseNet architecture while adding the ability to operate in a transformation invariant way while simultaneously being simpler than other models that try to provide some form of invariance.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 34 of its 45 references that are in the map. First posted on arXiv 23 Apr 2022.

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34 of 45 references.

References · 34

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  5. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  6. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  7. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  8. 2020End-to-End Object Detection with Transformerscited by 7,384
  9. 2016Densely Connected Convolutional Networkscited by 6,691
  10. 2020Training data-efficient image transformers & distillation through attentioncited by 4,560
  11. 2020Longformer: The Long-Document Transformercited by 3,362
  12. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,801
22 more
  1. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  2. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,960
  3. 2021ViViT: A Video Vision Transformercited by 1,610
  4. 2021Is Space-Time Attention All You Need for Video Understanding?cited by 1,609
  5. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,552
  6. 2020Linformer: Self-Attention with Linear Complexitycited by 1,462
  7. 2015Spatial Transformer Networkscited by 1,423
  8. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,218
  9. 2021Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetcited by 1,096
  10. 2018Image Transformercited by 770
  11. 2020A Survey on Visual Transformercited by 653
  12. 2021ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biasescited by 484
  13. 2018Rotation Equivariant CNNs for Digital Pathologycited by 420
  14. 2019Axial Attention in Multidimensional Transformerscited by 350
  15. 2021Medical Transformer: Gated Axial-Attention for Medical Image Segmentationcited by 319
  16. 2021Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encodingcited by 207
  17. 2016Deep Learning for Identifying Metastatic Breast Cancercited by 93
  18. 2017Detecting Cancer Metastases on Gigapixel Pathology Imagescited by 51
  19. 2020Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Imagescited by 33
  20. 2018Dermatologist Level Dermoscopy Skin Cancer Classification Using Different Deep Learning Convolutional Neural Networks Algorithmscited by 11
  21. 2020Cancer image classification based on DenseNet modelcited by 3
  22. 2019Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensorflow and Comparison of Performance for Various Hidden Layerscited by 2

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