Skip to content
ModelListedExternal
Browse files

Brain Tumor Efficientnetb3

4-class T1-weighted brain MRI classifier (glioma, meningioma, notumor, pituitary). Reproduces the best model from an IEEE 2024 paper (DOI: 10.1109/ICC-ROBINS60238.2024.10533941) and extends it with production...

Sourcehuggingface.co/Udit013/brain-tumor-efficientnetb3/tree/9841eb100cd9a3a168bcfdc80cf719053275d608
KindOtherVersionRevision 9841eb1Cgrade

Model source

Kind
Other
File size
44.3–45.1 MB
Version
vRevision 9841eb1
Updated
Nov 2, 2026
Downloads
0
Source
Hugging Face

Source description

EfficientNetB3 Brain Tumor MRI Classifier

4-class T1-weighted brain MRI classifier (glioma, meningioma, notumor, pituitary). Reproduces the best model from an IEEE 2024 paper (DOI: 10.1109/ICC-ROBINS60238.2024.10533941) and extends it with production evaluation. Input: 256x256x3 RGB, raw [0,255] pixels (EfficientNet rescales internally). Files: efficientnetb3.onnx (serving), EfficientNetB3_model_weights.h5 (Grad-CAM), temperature.json (calibration T).

Not a medical device — research/education only; dataset has documented train/test leakage. Full evaluation + code: https://github.com/Udit013/Brain_Tumor_Classificatioin

Sources

1 source
Hugging FacePrimaryVersion 9841eb100cd9a3a168bcfdc80cf719053275d608
huggingface.co/Udit013/brain-tumor-efficientnetb3/tree/9841eb100cd9a3a168bcfdc80cf719053275d608

Verified Nov 2

Download files

Repository files

File inventory only; completeness is unverified.

Model artifacts

2 artifacts

EfficientNetB3_model_weights.h5

h5 · 45.1 MB · SHA-256 d2ba7de13b7d…c2dd · Hugging Face

Download file

efficientnetb3.onnx

onnx · 44.3 MB · SHA-256 2a4c1f377970…5a97 · Hugging Face

Download file

Source excerpts

2 excerpts
ReadmeAug 19huggingface.co/Udit013/brain-tumor-efficientnetb3

--- license: mit tags: [image-classification, medical-imaging, brain-tumor, efficientnet, onnx] library_name: keras --- # EfficientNetB3 Brain Tumor MRI Classifier 4-class T1-weighted brain MRI classifier (glioma, meningioma, notumor, pituitary). Reproduces the best model from an IEEE 2024 paper (DOI: 10.1109/ICC-ROBINS60238.2024.10533941) and extends it with production evaluation. Input: 256x256x3 RGB, raw [0,255] pixels (EfficientNet rescales internally). Files: `efficientnetb3.onnx` (serving), `EfficientNetB3_model_weights.h5` (Grad-CAM), `temperature.json` (calibration T). **Not a medical device** — research/education only; dataset has documented train/test leakage. Full evaluation + code: https://github.com/Udit013/Brain_Tumor_Classificatioin

NoteAug 19huggingface.co/Udit013/brain-tumor-efficientnetb3

Source context: 0 downloads · 0 likes · Pipeline image-classification · Library keras · Repo Udit013/brain-tumor-efficientnetb3