I am doing cardiomegaly detection using deep learning.Is it possible to extract features using autoencoders and give it as input to an ensemble model
I am doing cardiomegaly detection using deep learning.Is it possible to extract features using autoencoders and give it as input to an ensemble model.Is it complex?and what would be the outcome would look like?
combine two class of image classifier together
I have made two model one for dog vs cat (also it tells the breeds) classification and other for vechicle classification(also it tell the model of car) is there a way to combine both these files so that I can use it to predict what i want (using the concept of API)
B-cos networks: Alignment is all we need
I am really interested topics like disentanglement and generative models and recently red this paper: https://arxiv.org/abs/2205.10268
I was wondering if replacing affine transformations by B-cos transformations (which is enforcing alignment between the weights and the input) could be benefitial in a generative setting. Furthermore, could it not be helpful to use these new layers to find disentangled latent factors? I was looking through all the citations but nobody uses B-cos networks in a generative framework. Maybe someone has more intuition about this topic or heard about related papers that already tried out similar stuff which he can share.
The first (and only problem) I see is, that the weight-input alignment is achieved by maximizing class logits in a classification problem. In a generative setting we will probably have a completly different loss function/optimization problem.
Machine learning versus deep learning – the similarities, the differences, the pros and cons
I read about AI and specifically ML and DL, and I can’t understand the diffrences.
In DL : what are the neurons? does the meaning I need some computers for DL? What are the layers?
I read this article and still with this questions.
I understand the DL is a subset of ML, but what are the similarities? because as my understanding those two subsets are different….
Supported ML Frameworks and Commanding NPU Execution on RK3588
I’m exploring running machine learning models on NPU RK3588. Could anyone share which ML frameworks are supported for this NPU? Additionally, I’d like to know how I can command the NPU to exclusively run models using these frameworks. Any insights or resources would be greatly appreciated!
Machine Learning: where to start the practice?
I’m taking a university course in ML and Big Data that I’m about to finish (end of this year), but we do very little practice and a lot of theory.