paper-with-me

홈 › Papers

Progressive Class-Wise Attention (PCA) Approach for Diagnosing Skin Lesions

2023-06-11 · Asim Naveed, Syed S. Naqvi, Tariq M. Khan, Imran Razzak

Skin cancer holds the highest incidence rate among all cancers globally. The importance of early detection cannot be overstated, as late-stage cases can be lethal. Classifying skin lesions, however, presents several challenges due to the many variations they can exhibit, such as differences in colour, shape, and size, significant variation within the same class, and notable similarities between different classes. This paper introduces a novel class-wise attention technique that equally regards each class while unearthing more specific details about skin lesions. This attention mechanism is progressively used to amalgamate discriminative feature details from multiple scales. The introduced technique demonstrated impressive performance, surpassing more than 15 cutting-edge methods including the winners of HAM1000 and ISIC 2019 leaderboards. It achieved an impressive accuracy rate of 97.40% on the HAM10000 dataset and 94.9% on the ISIC 2019 dataset.

📄 PDF Abstract BibTeX arXiv:2306.07300

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Visualizing CoAtNet Predictions for Aiding Melanoma Detection

2022-05-21 · Daniel Kvak

Melanoma is considered to be the most aggressive form of skin cancer. Due to the similar shape of malignant and benign cancerous lesions, doctors spend considerably more time when diagnosing these findings. At present, t…

Multi-class Classification

An Attention-Guided Deep Learning Approach for Classifying 39 Skin Lesion Types

2025-01-10 · Sauda Adiv Hanum, Ashim Dey, Muhammad Ashad Kabir

The skin, as the largest organ of the human body, is vulnerable to a diverse array of conditions collectively known as skin lesions, which encompass various dermatoses. Diagnosing these lesions presents significant chall…

DiagnosticPrognosisSpecificity

Data Augmentation for Skin Lesion using Self-Attention based Progressive Generative Adversarial Network

2019-10-25 · Ibrahim Saad Ali, Mamdouh Farouk Mohamed, Yousef Bassyouni Mahdy

Deep Neural Networks (DNNs) show a significant impact on medical imaging. One significant problem with adopting DNNs for skin cancer classification is that the class frequencies in the existing datasets are imbalanced. T…

Cancer ClassificationData AugmentationGeneral ClassificationGenerative Adversarial Network+1

Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification

2025-01-30 · Rafiul Islam, Jihad Khan Dipu, Mehedi Hasan Tusar

With over 2 million new cases identified annually, skin cancer is the most prevalent type of cancer globally and the second most common in Bangladesh, following breast cancer. Early detection and treatment are crucial fo…

Cancer ClassificationDecision MakingDeep LearningSkin Cancer Classification

Dynamic Sub-Cluster-Aware Network for Few-Shot Skin Disease Classification

2022-07-03 · Shuhan LI, Xiaomeng Li, Xiaowei Xu, Kwang-Ting Cheng

This paper addresses the problem of few-shot skin disease classification by introducing a novel approach called the Sub-Cluster-Aware Network (SCAN) that enhances accuracy in diagnosing rare skin diseases. The key insigh…

ClassificationClusteringFew-Shot LearningRepresentation Learning+1