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spectral-mamba-analysis

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software/spectral-mamba-analysis

Comparative spectral analysis of CNNs, Transformers, and State Space Models for medical image segmentation. Introduces AVR-based spectral fingerprinting across architecture paradigms.

Machine-generated from the listed sources and not yet reviewed by a human.

spectral-mamba-analysis project image
GitHub preview card for Subkash2206/spectral-mamba-analysis. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
active
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
alias-violation-ratio · boundary-segmentation · computer-vision · deep-learning · mamba-state-space-models · medical-image-segmentation · pytorch · spectral-analysis
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

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    [MedIA 2025] MambaMIM: Pre-training Mamba with State Space Token Interpolation and its Application to Medical Image Segmentation

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  • SE-Attention-Half-UNetcomputer-vision · medical-image-segmentation · pytorch

    Implementation of a compact Attention Half U-Net with Attention Gates and Squeeze-and-Excitation blocks for medical image segmentation. Features a modular PyTorch pipeline, BCE-Dice hybrid loss,…

  • DA-MambaNetmamba-state-space-models · medical-image-segmentation

    A lightweight medical image segmentation model that combines Mamba-based state-space modeling with efficient CNN modules to capture both global context and local features. The architecture is highly…

sources
  1. api.github.com/repos/Subkash2206/spectral-mamba-analysis
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2026-05-13, 5 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

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/v1/entries/33.json→ .entries["spectral-mamba-analysis"]

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