Questions tagged [deep-learning]

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How to prepare different input size in CNN

I'm doing a research about personality identification based on their signature using CNN method, however the learning feature for the personality traits have a different input size. I understand that ...
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0answers
31 views

Adversarial training: deep learning book

In the Deep Learning book of Ian Goodfellow, p. 261 it is shown how to build an "adversarial example" by adding to an image $x$ another image $x_{adversarial}$ build as epsilon times and image (same ...
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2answers
130 views

Augmentation for EEG signal classification using Deep Learning

Augmentation is a technique that we use in deep learning for expanding the training dataset. It includes different ways of modifying an image and adding it to the training dataset. My question is if ...
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0answers
75 views

Pose-invariant face detection and recognition

I would like to detect faces and later apply recognition algorithms to surveillance videos. Ideally, the application should run in real-time (or near real-time) and transfer the data first to an ...
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0answers
2k views

Image preprocessing for facial detection->embedding->clustering pipeline

I am trying to implement an end to end pipeline for facial clustering so that it can group people with the same faces. This will be quote a long post as I know that this is a very broad topic, so I ...
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0answers
6 views

How to implement a single shot object detector with only “one” anchor box per feature-map cell

I am newbie to SSD model, I have some images of products on a shelf , I trying to detecting that products using SSD with one anchor box per feature map, please help me out, how to prepare the data and ...
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0answers
12 views

How would one obtain 3D coordinates from 2D coordinates as well as the roll, pitch and yaw values of the observing camera?

I am trying to decipher the ParkNet DNN introduced by Nvidia. With no research paper released, this is proving quite a hassle. Right at the end of the blog post, it is mentioned that, using the roll ...
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0answers
12 views

Difference among motion vector, motion field and optical flow

I have started working on real-time recognition with deep learning and I read in many articles that optical flow can't work in real-time with deep neural networks, because of computational time. I ...
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0answers
29 views

Audio in Image,Graph or WaveForm Representation

Our task is to feed the audio data into the deep learning tensor flow model in the form of image representation(or graphical,waveform). Question is what is the best way of representing audio in image ...
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0answers
172 views

Understanding liftering as the final step in MFCCs features extraction

In the book here, they apply liftering, as a final step of MFCCs features extraction, to isolate the system component by multiplying the whole cepstrum by a rectangular window centred on lower ...
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0answers
37 views

Deep Learning based NDA Channel Estimation

I was wondering if it is possible to use Deep Learning to estimate the Channel Impulse Response for NDA synchronization? I understand Deep Learning is not normally used for regression problems but I ...
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0answers
21 views

Targets for Deep Neural Network in acoustic model for speech recognition

I'm trying to come up to speed on the use of deep neural networks for speech recognition and I'm confused about what exactly are the targets for the DNN. I understand that the DNN tries to predict a ...
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35 views

convolutional deep Neural Networks for matrix

I have a basic question about using convolutional neural networks. It's not my field but I'd like to read and understand about it. What I know that convolutional neural networks is used for image ...
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0answers
20 views

Does class imbalance affects for 1D CNNs?

I'm trying to develop a 1D CNN model for a high imbalance dataset. I tried giving sample_weights trying to compensate for the class imbalance. But it always classifies into one class.