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33 search results found

Interviews.ai ⭐ 3,146

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.

Pytorch Center Loss ⭐ 842

Pytorch implementation of Center Loss

Class Balanced Loss Pytorch ⭐ 740

Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

Deep_metric ⭐ 683

Deep Metric Learning

Stylegan Encoder ⭐ 588

StyleGAN Encoder - converts real images to latent space

Amsoftmax ⭐ 422

A simple yet effective loss function for face verification.

Learning to Cluster. A deep clustering strategy.

Deeptrade ⭐ 211

A LSTM model using Risk Estimation loss function for stock trades in market

Focal Loss Keras ⭐ 195

Binary and Categorical Focal loss implementation in Keras.

2dimageto3dmodel ⭐ 190

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.

Dl_note ⭐ 155

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

Pytorch_optimizer ⭐ 149

optimizer & lr scheduler & loss function collections in PyTorch

Pytorch Multi Class Focal Loss ⭐ 132

An (unofficial) implementation of Focal Loss, as described in the RetinaNet paper, generalized to the multi-class case.

Active Contour Loss ⭐ 117

Implementation of active contour loss function

Sphereface ⭐ 95

🍑 This is a MNIST Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR 2017

Focal Loss ⭐ 70

TensorFlow implementation of focal loss

I will implement Fastai in each projects present in this repository.

Improving MMD-GAN training with repulsive loss function

Semantic Segmentation With Mobilenetv3 ⭐ 50

TensorFlow (Keras) implementation of MobileNetV3 and its segmentation head

Dccrn With Various Loss Functions ⭐ 50

DCCRN with various loss functions

Official repository for "Orthogonal Projection Loss" (ICCV'21)

Balanced Loss ⭐ 43

Easy to use class balanced cross entropy and focal loss implementation for Pytorch

Bias Loss Skipblocknet ⭐ 30

[ICCV 2021]Code for the the bias loss and evaluation of SkipblockNet model on ImageNet validation set

IQA: Deep Image Structure and Texture Similarity Metric

Giouloss_ciouloss_caffe ⭐ 23

Caffe version Generalized & Distance & Complete Iou loss Implementation for Faster RCNN/FPN bbox regression

Regression Loss Functions In Time Series Forecasting Tensorflow ⭐ 22

This repository contains the implementation of paper Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting with different loss functions in Tensorflow. We have compared 14 regression loss functions performance on 4 different datasets.

Keras implementation of "DFNet: Discriminative feature extraction and integration network for salient object detection"

Nce Loss ⭐ 18

Tensorflow NCE loss in Keras

Soft Dtw Loss ⭐ 18

PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA

LossHub: Loss Functions Library for Image Classification and Detection

Tf_seq2seq_losses ⭐ 10

TensorFlow implementations of losses for sequence to sequence machine learning models

Polyloss Pytorch ⭐ 8

Polyloss Pytorch Implementation

Corel2019 ⭐ 8

Code for AAAI 2019 Network Interpretability workshop paper

Utilities for Deep Learning with PyTorch (models, losses, metrics etc.)

Gradient Variance Loss ⭐ 7

Code of the ICASSP 2022 paper "Gradient Variance Loss for Structure Enhanced Super-Resolution"

We aim to generate realistic images from text descriptions using GAN architecture. The network that we have designed is used for image generation for two datasets: MSCOCO and CUBS.

Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction

Official PyTorch implementation for "PROPEL: Probabilistic Parametric Regression Loss for Convolutional Neural Networks"

Nn Additional Losses ⭐ 5

A collection of losses not part of pytorch standard library particularly useful for segmentation task

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