Questions tagged [deep-learning]
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28
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30 views
Which Machine or deep learning algorithm is appropriate of this issue?
Suppose I have $n$ features as $Y$ = ($y_1 , y_2 ...., y_n$), and a matrix of $J$ of dimension $M$x$N$, one feature of $Y$ is selected randomly to be convoluted with one random column of $J$ resulting ...
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12 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.
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1answer
14 views
Are delta and double delta features needed when classifying with LSTM
I understand that the combination of MFCCs, deltas and double deltas is a good feature to be used with HMMs for keyword detection problems. HMMs are limited by Markov Property and this limitation is ...
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2answers
30 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
28 views
How to express STFT and ISTFT as a 1d convolution and 1d deconvolution in tensorflow/keras
I'm trying to implement this paper in tensorflow and keras. At the end of section 3 it says.
...
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9 views
Pascal Voc 2012 Annotaions for 6D viewpoint(pose) estimation
Everyone, I am working on 6D pose estimation and I have to predict a rotation matrix (Euler angle) and translation.
Now In Pascal Voc annotations are in the form of azimuth, elevation and distance ...
1
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2answers
76 views
audio spectrogram normalization
I am performing language classification from audio signals using mel-spectrograms as my inputs for a ResNet. It works well as long as all of my audio data from different languages is from the same ...
0
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1answer
25 views
What does it mean for a Wavelet transform to commute with translations?
Referencing this article here https://arxiv.org/pdf/1203.1513.pdf
It states "A wavelet transform commutes with translations, and is therefore not translation invariant". Now I understand why it is a ...
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0answers
28 views
Disabled parking sign detection
I would like to ask you, if you could recommend some algorithm for detection of handicapped or disabled parking sign painted on the road or on the traffic sign.
I am thinking about image morphology (...
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0answers
23 views
problem in selecting correct algorithm for project (RCNN)
I am doing a deep learning project in which i have to identify different models of cars.
i am a bit confused for the following reason:
first is what algorithm should I use. I have studied that RCNNs ...
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2answers
52 views
What fps can be considered as a hardline for real-time performance? Is there any academic paper that describes this?
I am trying to design a deep learning based inferencing solution for security applications. My deployed program achieves an FPS of 15fps for classification. Can it be considered real-time?
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2answers
1k views
Neural Networks and Complex Valued Inputs
[not sure if this or stats.stackexchange was the correct location for this post, so put it on both for now.]
I've seen some recent papers describing complex valued neural networks like this one: Deep ...
2
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1answer
103 views
Is deep learning the only way to detect humans in a picture?
I'm looking for a way to detect humans in a picture. For instance, regarding the picture below, I'd like to coarsely determine how many people are in the scene. I must be able to detect both standing ...
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1answer
72 views
In Convolutional Neural Nets, what do convolutions look like?
The early stages of the Convolutional Neural Networks are performing classical convolutions with a certain kernel size on the input image. Is is possible to express in common terms the type of ...
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1answer
49 views
Does the audio signal in the time domain change much after a RMS from one person to another?
I would like to train a deep neural network to perform lip syncing given an audio input like in this article.
I want to train my neural network only on Obama speeches like done in the article and ...
2
votes
1answer
251 views
RNN as posterior probability estimation in speech recognition with HTK
I'm new to speech recognition and deep learning and in a learning phase.
I'm trying to follow this paper to learn how to use RNN as posterior probability estimation in an HTK environment. The paper ...
2
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1answer
738 views
Training a CNN-HMM model
I am currently trying to train a CNN-HMM acoustic model for speech recognition.
The CNN model is able to detect a center monophone given a context window of x (limits has not been tested yet - but ...
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1answer
47 views
Deep learning model for phone recognition - issues with dimension the model
I seem to have some problems understandind how the model described in this paper has been designed
This is what is written about the model dimension..
...In these experiments we used one ...
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0answers
67 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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1answer
128 views
image reconstruction using a set of kernels
I try to be brief. For what I understood Convolutional Neural Network CNN for style-transfer extract/learn the main features of source Image. I think these features basically are Kernels (of different ...
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1answer
411 views
Is image annotation a hard AI problem? [closed]
From Wikipedia "In the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems is ...
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3answers
1k views
Principal Component Analysis (PCA) on Convolutional Neural Network (CNN) Features
Please, I have a question regarding PCA and features which are extracted from a convolutional layer. link
if we have a test dataset , and we extract all conv features of all images at test dataset ...
2
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1answer
6k views
When is a network called end-to-end training?
In machine learning, we often see the expression "end-to-end" learning (or training). However, I do not know that it means. When is a network called end-to-end training? How to recognize a network is ...
4
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2answers
7k views
Can deep neural networks achieve real-time video analysis?
Recently, convolutional neural network based, deep architectures (DNN) such as AlexNet and VGGnet have been very successful in image classification challenges (e.g. ImageNet) and action recognition/...
49
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10answers
14k views
Is deep learning killing image processing/computer vision?
I'm looking forward to enroll in an MSc in Signal and Image processing, or maybe Computer Vision (I have not decided yet), and this question emerged.
My concern is, since deep learning doesn't need ...
0
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1answer
61 views
neural network for 3D pictures
I'm wondering if they are some state-of-art algorithms to apply the convolutional neural network approach to 3D pictures, eg. input is no longer a grid of pixels, but voxels. My objective is to ...
2
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1answer
274 views
Opinion about this aproach on Machine Learning
I have a question for you that maybe you could give me a clue.
I'm trying to make a CBIR (Content-Based Image Retrieval), so I query an image and I get the most similar, not classified within a ...
