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It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
Code for the Lovász-Softmax loss (CVPR 2018)
Pytorch implementation of Center Loss
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Collection of audio-focused loss functions in PyTorch
A simple yet effective loss function for face verification.
Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)
深度学习系统笔记,包含深度学习数学基础知识、神经网络基础部件详解、深度学习炼丹策略、模型压缩算法详解。
IQA: Deep Image Structure and Texture Similarity Metric
A LSTM model using Risk Estimation loss function for stock trades in market
Learning to Cluster. A deep clustering strategy.
Comparison of IQA models in Perceptual Optimization
Binary and Categorical Focal loss implementation in Keras.
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An unofficial Gluon FR Toolkit for face recognition. https://gluon-face.readthedocs.io
An (unofficial) implementation of Focal Loss, as described in the RetinaNet paper, generalized to the multi-class case.
Reproducing experimental results of LL4AL [Yoo et al. 2019 CVPR]
Implementation of active contour loss function
TensorFlow implementation of focal loss