If we want to classify something as either a cat/dog or neither, do we need 2...
Suppose one trains a CNN to determine if something was either a cat/dog or neither (2 classes), would it be a good idea to assign all cats and dogs to one class and everything else to another? Or would...
View ArticleImage Classification for watermarks with poor results
Just starting learning things about tensorflow and NN.As an exercise I decided to create a dataset of images, watermarked and not, in order to binary classify these. First of all, the dataset ( you can...
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How to use residual learning applied to fully connected networks?
Is there any reason why skip connections would not provide the same benefits to fully connected layers as it does for convolutional?I've read the ResNet paper and it says that the applications should...
View ArticleSupport Vector Machine Convert optimisation problem from argmax to argmin
I'm new to the AI Stackexchange and wasn't certain if this should go here or to Maths instead but thought the context with ML may be useful to understand my problem. I hope posting this question here...
View ArticleShould binary feature be in one or two columns in deep neural networks?
Let's assume I have a simple feedforward neural network whose input contains binary 0/1 features and output is also binary two classes.Is it better, worse or maybe totally indifferent, for every of...
View ArticleIs it a fair evaluation if each model of k-fold cross validation is trained...
Let's say I have a dataset for binary classification. And I am going to conduct 5-fold cross-validation and get AUC scores for each fold (mean AUC score too). However, if I set the training epoch to...
View ArticleHow many parameter would there be in a logistic regression model used to...
Suppose we want to classify a review as good ($1$) or bad ($0$). We have a training data set of $10,000$ reviews. Also, suppose we have a vocabulary of $100,000$ words $w_1, \dots, w_{100,000}$. So the...
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How to perform data augmentation on multiple input classification task?
I would like to add some more samples to my dataset which consists of two parts: 1. image and 2. numerical data. For each image in the dataset there is its corresponding numerical data as well.If it...
View ArticleSemantic segmentation failing in small instance detection
I performed semantic segmentation with U-net. My dataset consists of grayscale images of defects. After training the dataset for I got an metric accuracy of only 0.3 - 0.4 IOU. Eventhough it is merely...
View ArticleAre there any advantages of using rules-based approaches versus models for...
Suppose that we have unlabeled data. That is, all we have are a collection of emails and want to determine whether any of them is spam or not. Let's say we have $1,000$ rules to determine whether a...
View ArticleWhy is my fine-tuned YOLO model detecting other objects as a human?
I am new to deep learning and computer vision. I have a problem where I use the YOLO to detect objects.For my problem, I just want to recognize 1 human only. So, I changed the final YOLO's layer (which...
View ArticleHow can I use Generative Adversarial Networks to solve the imbalanced class...
Problem settingWe have to do a binary classification of data given a training dataset $D$, where most items belong to class $A$ and some items belong to class $B$, so the classes are heavily...
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Why doesn't the set $\{ -2, +2 \}$ in $E(X) = (y − \text{sign}\{\overline{W}...
I am currently studying the textbook Neural Networks and Deep Learning by Charu C. Aggarwal. Chapter 1.2.1.2 Relationship with Support Vector Machines says the following:The perceptron criterion is a...
View ArticleWhat is the definition of the hinge loss function?
I came across the hinge loss function for training a neural network model, but I did not know the analytical form for the same.I can write the mean squared error loss function (which is more often used...
View ArticleWhy am I getting a difference between training accuracy and accuracy...
I'm trying to solve a binary classification problem with AlexNet. I split the original dataset into training and validation datasets using a 70/30 ratio. I have trained my neural network with a dataset...
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Why are CNN binary classifier output probability distributions often skewed?
I've been working on a lot of simple resnet18 binary classifiers lately and I've started to notice that the probability distributions are often skewed one way or the other. This figure shows one such...
View ArticleWhich approach should I use to classify points above and below a sine...
In a linear regression problem, a line can divide a data set into two categories. So, basically, points above the line belong to category 1, and points below the line belong to category -1.However, my...
View ArticleShould an increased learning rate for an adaptive linear neuron (ADALINE)...
I am completely new to neural networks and therefore, my query may have some basic conceptual problem.I am following Fundamentals of Neural Networks by Laurene Fusett. In this book, the author...
View ArticleIs it appropriate to use a softmax activation with a categorical crossentropy...
I have a binary classification problem where I have 2 classes. A sample is either class 1 or class 2 - For simplicity, lets say they are exclusive from one another so it is definitely one or the...
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How should we interpret this figure that relates the perceptron criterion and...
I am currently studying the textbook Neural Networks and Deep Learning by Charu C. Aggarwal. Chapter 1.2.1.2 Relationship with Support Vector Machines says the following:The perceptron criterion is a...
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