Search Results for author: Aravindan Chandrabose

Found 6 papers, 1 papers with code

An Overview of Fairness in Data – Illuminating the Bias in Data Pipeline

no code implementations EACL (LTEDI) 2021 Senthil Kumar B, Aravindan Chandrabose, Bharathi Raja Chakravarthi

Data in general encodes human biases by default; being aware of this is a good start, and the research around how to handle it is ongoing.

Fairness

Few-Shot Classification of Skin Lesions from Dermoscopic Images by Meta-Learning Representative Embeddings

1 code implementation30 Oct 2022 Karthik Desingu, Mirunalini P., Aravindan Chandrabose

Specifically, we propose a baseline supervised method on the meta-training set that allows a network to learn highly representative and generalizable feature embeddings for images, that are readily transferable to new few-shot learning tasks.

Few-Shot Learning

SSN\_NLP at SemEval-2020 Task 7: Detecting Funniness Level Using Traditional Learning with Sentence Embeddings

no code implementations SEMEVAL 2020 Kayalvizhi S, Thenmozhi D., Aravindan Chandrabose

For subtask 2, Universal sentence encoder classifier achieves the highest accuracy for development set and Multi-Layer Perceptron applied on vectors vectorized using universal sentence encoder embeddings for the test set.

Sentence Sentence Embeddings

Deep Learning for Skin Lesion Classification

no code implementations13 Mar 2017 P. Mirunalini, Aravindan Chandrabose, Vignesh Gokul, S. M. Jaisakthi

Our system learns to classify the images based on the model built using the training images given in the challenge and the experimental results were evaluated using validation and test sets.

Classification General Classification +3

Automatic Skin Lesion Segmentation using Semi-supervised Learning Technique

no code implementations13 Mar 2017 S. M. Jaisakthi, Aravindan Chandrabose, P. Mirunalini

In the preprocessing phase noise are removed using filtering technique and in the segmentation phase skin lesions are segmented based on clustering technique.

Clustering Lesion Segmentation +2

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