Seesaw Loss
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Understanding Seesaw Loss: A Dynamic Loss Function for Long-Tailed Instance Segmentation
Instance segmentation is a crucial task in computer vision…
Metric mixup
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In the world of deep learning, accuracy is essential. One way to improve accuracy is by using Metrix, a powerful…
Varifocal Loss
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Varifocal Loss is a loss function that is used to train a dense object detector to predict the Intersection over…
Multi Loss ( BCE Loss + Focal Loss ) + Dice Loss
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A Comprehensive Overview of Multi Loss Functions (BCE Loss + Focal Loss + Dice Loss)
When it comes to image segmentation tasks,…
Unsupervised Feature Loss
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What is UFLoss?
UFLoss, or Unsupervised Feature Loss, is a type of deep learning (DL) model used for reconstructions. It…
Dual Softmax Loss
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Dual Softmax Loss is a loss function that is commonly used in video-text retrieval models such as CAMoE. This loss…
Supervised Contrastive Loss
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Supervised Contrastive Loss is a method used in machine learning to better analyze and group data. It is a type…
PIoU Loss
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PIoU Loss is a type of loss function used in the process of oriented object detection. It is aimed at…
Triplet Entropy Loss
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Triplet Entropy Loss: Improving the Training Process
In the field of machine learning, neural networks are trained using various methods…
Dynamic SmoothL1 Loss
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Dynamic SmoothL1 Loss (DSL) is a loss function used in object detection to improve the accuracy of locating objects in…
Generalized Focal Loss
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What is Generalized Focal Loss?
Generalized Focal Loss (GFL) is a loss function used in object detection. It combines two…
Balanced L1 Loss
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Balanced L1 Loss: A Comprehensive Overview
In the field of machine learning, one of the major tasks is object detection.…
Self-Adjusting Smooth L1 Loss
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What is Self-Adjusting Smooth L1 Loss?
Self-Adjusting Smooth L1 Loss is a concept used in object detection that involves minimizing…
Lovasz-Softmax
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Lovasz-Softmax: An Overview
The Lovasz-Softmax loss is a special case of the Lovasz extension and has become particularly popular in…
Gradient Harmonizing Mechanism C
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What is GHM-C?
GHM-C, which stands for Gradient Harmonizing Mechanism for Classification, is a type of loss function used in…
Gradient Harmonizing Mechanism R
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What is GHM-R?
GHM-R is a loss function that is used to improve the training of artificial intelligence (AI) models.…
Triplet Loss
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Overview of Triplet Loss in Siamese Networks
Triplet loss is a method used in Siamese Networks to maximize the likelihood…
InfoNCE
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InfoNCE, which stands for Noise-Contrastive Estimation, is a loss function utilized in self-supervised learning. This approach aims to train a…
Early exiting using confidence measures
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Early Exiting: Optimizing Neural Networks for Efficient Learning
Efficient and fast learning is one of the key goals in artificial…
Additive Angular Margin Loss
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ArcFace, also known as Additive Angular Margin Loss, is a loss function used in face recognition tasks. Its purpose is…
Dice Loss
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Dice Loss: A Comprehensive Overview
Dice Loss is an important concept in the field of computer vision, specifically in image…
Adaptive Robust Loss
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Adaptive Loss: Improving Performance on Basic Vision and Learning-Based Tasks
What is Adaptive Loss?
Adaptive Loss is a type of…
VGG Loss
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VGG Loss is a content loss method for super-resolution and style transfer. It aims to be more similar to human…
WGAN-GP Loss
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Overview of WGAN-GP Loss
Generative Adversarial Networks (GANs) are a popular machine learning model used in various applications such as…
Normalized Temperature-scaled Cross Entropy Loss
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NT-Xent, also known as Normalized Temperature-scaled Cross Entropy Loss, is a loss function used in a variety of machine learning…
Connectionist Temporal Classification Loss
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Understanding CTC Loss: A Guide for Beginners
Connectionist Temporal Classification, more commonly referred to as CTC Loss, is a deep…
GAN Hinge Loss
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GAN Hinge Loss is a technique used in Generative Adversarial Networks (GANs) to improve their performance. GANs are a type…
Focal Loss
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Focal Loss: An Overview
When training a model to detect objects, there is often an imbalance in the number of…
Cycle Consistency Loss
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The concept of Cycle Consistency Loss is commonly used for generative adversarial networks that perform unpaired image-to-image translation. This loss…
GAN Least Squares Loss
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The GAN Least Squares Loss is an objective function used in generative adversarial networks (GANs) to improve the accuracy of…