Focal Loss

Latest papers

8 papers1 paper in the last four weeks, with none the four weeks before. 0.0% of all new papers.

On Impact of Loss Function on the Performance of Neural Networks in Melanoma Diagnosis
Oct 5, 2026Morgan May, Pierpaolo Dondio, Simon CatonClass-Imbalanced Learning Skin Lesion Classification
Technological University Dublin, Dublin, Ireland · Research Ireland Centre for Research Training in Machine Learning, ML-Labs, Dublin, Ireland · Dublin City University, Dublin, Ireland +1
Twins: Learn to Predict Unified Representations with Focal Loss
Jul 24, 2026Kaixiong Gong, Xin Cai, Bin Lin +9Focal Loss Diffusion Transformer
The Chinese University of Hong Kong · Tencent, Hunyuan · City University of Hong Kong +2
Parameter-efficient Prompt Tuning of Vision Foundation Model With Adaptive Focal Loss for Interpretable MCI Screening
Jul 16, 2026Javad Khoramdel, Farhad Hoseyni, Amirhossein NikoofardClass-Imbalanced Learning Focal Loss
APAC Research Group, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
A time-series classification framework for individual-level absenteeism prediction under severe class imbalance
Jun 30, 2026Kwong Ho Li, Matthew Roughan, Wathsala KarunarathneClass-Imbalanced Learning Focal Loss
School of Mathematical Sciences, Adelaide University, SA 5000, Australia
An Empirical Analysis of Optimization Dynamics and Sparsity Boundaries in Large-Scale Pedestrian Attribute Recognition
Jun 9, 2026Houssam El MirClass-Imbalanced Learning Focal Loss
College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, China
Diversity in Large Language Models under Supervised Fine-Tuning
Apr 30, 2026Roman Klypa, Oleksandr CherednichenkoSupervised Fine-Tuning Focal Loss
Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK, 38000 Grenoble, France · Department of Mathematics and Mathematical Statistics, Integrated Science Lab, Umeå University, Sweden.
Functional Properties of the Focal-Entropy
Mar 3, 2026Jaimin Shah, Martina Cardone, Alex DytsoFocal Loss Class-Imbalanced Learning
University of Minnesota, USA · Qualcomm Flarion Technology, Inc., USA
A Novel GPT-Based Framework for Anomaly Detection in System Logs
Oct 16, 2025Zeng Zhang, Wenjie Yin, Xiaoqi LiFocal Loss Anomaly Detection
Hainan University Haikou, China

Oct 5, 2026J/K move · Enter open · S save

On Impact of Loss Function on the Performance of Neural Networks in Melanoma Diagnosis

Morgan May, Pierpaolo Dondio, Simon Caton

Technological University Dublin, Dublin, Ireland · Research Ireland Centre for Research Training in Machine Learning, ML-Labs, Dublin, Ireland · Dublin City University, Dublin, Ireland+1

Class-Imbalanced Learning Skin Lesion Classification Focal Loss

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Melanoma is the deadliest type of skin cancer, whose early diagnosis is crucial for patients' survival. Image classification using deep learning models has shown promising results for melanoma diagnosis. However, the performance of these models on the melanoma datasets such as SIIM-ISIC melanoma classification dataset is a challenge due to the class imbalance. One of the methods to deal with this challenge is using loss function modifications. In this work, we have investigated the effect of different loss functions on the performance of deep neural networks. We trained these networks using focal loss, logit-adjusted softmax cross-entropy (CE) loss, and weighted softmax CE loss, and we report different metrics for evaluating performance and uncertainty calibration. Our results suggest that focal loss delivers a good combination of performance in terms of AUC and uncertainty calibration in terms of expected calibration error (ECE) simultaneously.