Hi,
i have a dataset with MRI of patients with a specific disease that affects the brain and another dataset with MRI of healthy patients.
I want to create a classifier (using neural networks) to classify if the MRI of a new patient show the presence of the ill or not.
First of all, i...
I would like to try RBF-ANN as the classifier.
Let me explain better. For the moment ignore my original question.
I have a dataset A of videos. I've extracted the feature vector of each video (with a convolutional neural network, via transfer learning) creating a dataset B. Now, every vector of...
Let's consider this scenario. I have two conceptually different video datasets, for example a dataset A composed of videos about cats and a dataset B composed of videos about houses. Now, I'm able to extract a feature vectors from both the samples of the datasets A and B, and I know that, each...
Yes but i don't understand the rules when dealing with infinitesimal quantities. It's the only thing i can't deeply understand in undergraduate physics and i haven't found a book about it.
ps: i think i have not understood why you have took care of this chain of disequalities: \pi r^2 dh < dV...
Why can we neglect those higher-order terms ? Furthemore, if we do this than \pi r^2 dh < dV < \pi (r + dr)^2 dh = \pi (r^2 +2rdr + dr^2)dh becomes pointless
ps: i think i have not understood why you have underlined this chain of disequalities
If i want to calculate the volume of a cone i can integrate infinitesimal disks on the height h of the cone.
I was told that if i want to calculate the surface of the cone, this approximation is not correct and i have to take the slanting into account, this means that instead of...
Yes, let's suppose that its a real system with the parameters a_{1},b_{0}, b_{1}, output y(t) and input x(t) and \Delta a_{1},\Delta b_{0},\Delta b_{1} are faults the parameters
I tried to derive this by myself but I'm stuck. What i did it to substitute a_{1} with a_{1} +\Delta a_{1} in the first equation, getting:
(a_{1}+\Delta a_{1})\dot{y}(t)+y(t)=b_{0}u(t)+b_{1}\dot{u}(t)
and trying to subtract a_{1}\dot{y}(t)+y(t)=b_{0}u(t)+b_{1}\dot{u}(t) to it. But it's not...
"Suppose we look at a molecule with mass m in a gas at temperature T and consider
first only the x-component of its velocity, vx. The value of vx taken on by a given molecule at
a given time will be the end result of a tremendous number of collisions, each of which changes
its vx by some random...