Questions tagged [performance]

For question about methods of evaluating the performance (e.g. the accuracy) of an artificial intelligence algorithm or model.

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How do you measure multi-label classification accuracy?

Multi-label assignment is the task in machine learning to assign to each input value a set of categories from a fixed vocabulary where the categories need not be statistically independent, so ...
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What is human-level performance for semantic segmentation?

I see so many papers claim to have an algorithm that beats 'human-level performance' for semantic segmentation tasks, but I can't find any papers reporting on what the human-level performance actually ...
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Can the addition of low-quality images to the training dataset increase the network performance?

I already trained a deep neural network called YOLO (You Only Look Once) with high-quality images (1920 by 1080 pixels) for a detection task. The result for mAP and IOU were 93% and 89% respectively. ...
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In addition to matrix algebra, can GPU's also handle the various Kernel functions for Neural Networks?

I've read a number of articles on how GPUs can speed up matrix algebra calculations, but I'm wondering how calculations are performed when one uses various kernel functions in a neural network. If ...
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0answers
41 views

Performance measure on windowed time series data

I have time series data where I use a sliding window to detect anomalies in those windows. A sliding window is an interval of the dataset that steps one datapoint for each iteration. Datapoints are ...
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1answer
43 views

Keras CNN: Multi Label Classification of Images - Model Evaluation

I am rather new to deep learning and got some questions on performing a multi-label image classification task with keras convolutional neural networks. Those are mainly referring to evaluating keras ...
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46 views

Which neural network architecture to use to detect very close and very small blobs in high resolution fluorescence images?

Context I am developing a pipeline to automate the detection of small, almost circular, bright blobs (4px) (see first image below) on high-resolution fluorescence images (2048px) and later to assign ...
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50 views

Are goal-reaching and optimizing the utility function special cases of performance measure?

In AIMA, performance measure is defined as something evaluating the behavior of the agent in an environment. Rational agents are defined as agents acting so as to maximize the expected value of the ...
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28 views

Identifying if a model is over or under-fitting via graphs

I am working on a Neural Network and have plotted the performance of my model. However the plots seem not to fit the "trends" (which help you identify the issue with your model) presented in ...
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0answers
61 views

Is the performance of a neural network, which was trained with encrypted data and weights, affected if the weights are decrypted?

Suppose that a neural network is trained with encrypted (for example, with homomorphic encryption and, more precisely, with the Paillier partial scheme) data. Moreover, suppose that it is also trained ...
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23 views

Would performance of atomic models matter in ensemble methods?

Suppose I have two fitted ensemble models $F_1 := (f_1, f_2, f_3, \cdots f_n)$ and $G_1 := (g_1, g_2, g_3, \cdots g_n)$. And they were using the same ensemble methods (boosting or bagging). And I am ...
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27 views

How is the performance of a CNN trained with monochrome images on image recognition tasks degraded?

For CNN image recognition tasks, like object recognition/face recognition/object segmentation/posture recognition, are there experiment results about how much will the performance be degraded with ...
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38 views

How many training runs are needed to obtain a credible value for performance?

I'm trying to optimize a neural network. For that, I'm changing parameters like the batch size, learning rate, weight initialization, etc. A neural network is not a deterministic algorithm, so, in ...
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39 views

Sample size for the evaluation of Deep Learning Models

I'm evaluating the performance and accuracy in detecting objects for my data set using three deep learning algorithms. In total there are 24,085 images. I measure the performance in terms of time ...
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23 views

What are the properties of a model that is well suited for for high performance real-time inference

What are general best practices or considerations in designing a model that is optimized for real-time inference?
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22 views

Improving Recall of a Certain Class

Let's say that we have a test data set with $20,000$ observations for which we want to make a binary prediction for. When we apply our best trained model to this data set (e.g. logistic regression ...
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0answers
35 views

Why does precision-recall curve become more stable when neural net begins to overfit?

I am training a convLSTM with a dropout layer (with prob 0.5). If I train over more than 5 epochs I notice that the network starts to overfit: my validation set loss becomes stationary while the ...
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34 views

How to visualize/interpret text prediction model results?

I am using LSTM model to predict the next xml markup from an input seed. I have trained my model on 1500 xml files. Each xml file is generated randomly. I am wondering if there is a way to visualize ...
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16 views

Simple example for average log-probability

Consider the following statements from Chapter 5: Machine Learning Basics from the book titled Deep Learning (by Aaron Courville et al.) For tasks such as classification, classification with missing ...
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11 views

How to properly report results for a medical image segmentation task?

Let’s consider a 2-class / binary segmentation problem where c=0 for background (healthy tissues) and c=1 for foreground (...
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16 views

Train a model for different scenario and gather performance results in a single place

Recently, I extend a master's thesis. I am now in a training phase for the model associated with it. I have access to many node GPUs. I would like to train this model on different scenarios, e.g. ...
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36 views

Why is the F-beta score not increasing while the validation loss fluctuates?

I'm trying to implement a multi-label image classification from a CT scan data set. The goal of the work is to find out which CT scan image has eleven of the most common fractures if it is fractured. ...
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175 views

What is the difference between learning agents and other kinds of agents, and more specifically, between performance standard and performance measure?

I am reading AI: A Modern Approach. In the 2nd chapter when introducing different agent types, i.e., reflex, utility-based, goal-based, and learning agents, I understood that all types of agents, ...
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1answer
55 views

Can the attention mechanism improve the performance in the case of short sequences?

I am aware that the attention mechanism can be used to deal with long sequences, where problems related to gradient vanishing and, more generally, representing effectively the whole sequence arise. ...
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93 views

What to do when an image classifier does good for a class but bad for another?

So I wrote a convolutional neural network for a binary image classification. I have around 5300 images for each class which I thought would be enough to at least give me a good accuracy on the ...