Questions tagged [computer-vision]

For questions related to computer vision, which is an interdisciplinary scientific field (which can e.g. use image processing techniques) that deals with how computers can be made to gain high-level understanding from digital images or videos. For example, image recognition (that is, the identification of the type of objects in an image) is a computer vision problem.

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3answers
265 views

Has anybody tried unsupervised deep learning from youtube videos?

YouTube has a huge amount of videos, many of which also containing various spoken languages. This would presumably provide something like the data that a "challenged" baby would experience - "...
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1answer
87 views

Extracting one class from a pretrained Convolutional Neural Network

I am new to deep learning and computer vision. I have a problem where i use yolo algorithm (https://pjreddie.com/) to detect objects. In the original paper, they define the output to recognize 80 ...
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Commercial API Q: is there an api for converting vision tags into a caption?

There are many machine learning api for scanning images but they just return a bunch of tags. https://azure.microsoft.com/en-gb/services/cognitive-services/computer-vision/ ...
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2answers
287 views

Algorithms for scene rotation

My goal is to take an image and return another image that looks as if the scene was viewed from another angle. The difference in angle can be small — let's say as if the hand holding the camera moved ...
2
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1answer
499 views

JavaScript Client Side GAN implementation

Recently I came across this website which is a year old: https://affinelayer.com/pixsrv/ On Desktop we can draw and download the trained model in browser and see the corresponding image generated on ...
5
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1answer
209 views

Other Deep Learning Networks for Visual Place Recognition?

I am doing a project on Visual Place Recognition in Changing Environments. The CNN used here is mostly AlexNet, and a feature vector is constructed from Layer 3. Does anyone know of similar work ...
3
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1answer
34 views

Executing trained image classification model for video

I've been working with vanilla feed forward neural networks and have been researching the convolutional neural network literature. Thus far I've have not encountered how often the model is executed in ...
3
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1answer
594 views

Training a Yes/No NN for Image Classes

I am fairly a newbie to Neural Networks. I wanted to ask if it is possible to train a NN to identify only one type object? For instance, a table from a large set of images, where the NN should be ...
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2answers
3k views

Training an AI to play Starcraft 2 with superhuman level of performance?

I'm interested in working on challenging AI problems, and after reading this article (https://deepmind.com/blog/deepmind-and-blizzard-open-starcraft-ii-ai-research-environment/) by DeepMind and ...
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3answers
1k views

What activation function is not used at the final layer of super resolution neural models?

I'm trying to implement some Image super-resolution models on medical images. After reading a set of papers, I found that none of the existing models use any activation layer for the last layer. What'...
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1answer
80 views

Is there a way of computing a prominence score based on the prevalence of features in an image?

Is there any previous work on computing some sort of prominence score based on the prevalence of features in an image? For example, let's say I am classifying images based on whether or not they have ...
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68 views

Data extraction from medical reports

I am new in Machine Learning. I have taken a course in vision and we are required to do a project. I am thinking of data mining medical lab report images. My code must take an image and jpg file ...
2
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1answer
59 views

Continuous ground truth in supervised (metric) learning?

I am writing my thesis in the field of (deep) metric learning (DML). I am training a network in the fashion of contrastive / triplet Siamese networks to learn similarity and dissimilarity of inputs. ...
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1answer
3k views

Confusion regarding anchor boxes in YOLO

I'm going through Andrew NG's course which talks about YOLO but he doesn't go into the implementation details of anchor boxes. Look through the code, each anchor box is represented by two values, but ...
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0answers
189 views

Extracting specific features using HOG

I am using HOG (Histogram of Oriented Gradients) for car detection from a video. I have used the Matlab function extractHOGFeatures() , it has given me a feature ...
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2answers
61 views

Searching an AI to recognize and locate persons in a factory

TLDR : Is there an AI available that can recognize employees in a factory and tell when they entered and left pre-defined areas? I work in a factory where we gather cycle time data from various ...
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2answers
136 views

Neural Network that Predicts Game State Based on Actions

I am trying to find literature on a network architecture that takes the following as in input: Action (like 'Up', 'Down', etc) Image of current state and outputs: Image of next state I already ...
2
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1answer
324 views

Is it possible to count the number of squats with Computer Vision techniques?

I am planning to build an app which will count the number of sqauts from videos. Assuming that the user and camera do not move, are there ways I can count the number of squats? Do such models to ...
2
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1answer
122 views

Tracking object

At this moment, I am able to use NN to identify object such as human when given a frame from the camera. Once locate the object, then I can feed the human object image to either NN that's designed to ...
3
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1answer
947 views

What is the difference between 'Pixel' based object recognition and 'Feature' based object recognition?

From my understanding and text I found in research papers online : 1) Pixel based object recognition: Neural networks are trained to locate individual objects based directly on pixel data. 2) ...
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1answer
33 views

Could a multi-camera SLAM system that is accurate at low driving speeds be equally accurate at high driving speeds?

Could a multi-camera SLAM system for self-driving cars that is accurate to under 10 cm (3.9 in) at parking lot speeds (i.e. very low driving speeds) retain this level of accuracy at high driving ...
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3answers
13k views

Measuring Object size using Deep Neural Network

I have a large dataset of vehicles with the ground truth of their lengths (Over 100k samples). Is it possible to train a deep network to measure/estimate vehicle length ? I haven't seen any papers ...
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0answers
37 views

Detecting symmetry in small images with RNN

My network works on 32x32 normalized (translationally) but noisy images. Its task it to determine whether image has simple symmetry (horizontal/vertical). It needs to be reasonably robust to rotation (...
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1answer
107 views

Object detection doubt

I asked this question on /r/learnmachinelearning, but there was no answer so I'm reposting it here. I was reading this article on detecting rectangles in an image, here. My doubt is in the part where ...
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0answers
55 views

How do cognitive services work?

Currently big tech companies like Microsoft, Google, and Amazon (to name a few) offer cognitive services on their cloud platforms. With these services it is possible to identify faces, objects, texts,...
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1answer
1k views

Can reinforcement learning algorithms be applied to computer vision problems?

Can reinforcement learning algorithms be applied to computer vision problems? If yes, what are some examples of these applications?
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2answers
309 views

Is there a computer vision service for classifying images on a fixed array of images provided by me?

I was checking services like Microsoft Azure's Cognitive Services Computer Vision API and Google's Vision API and they are amazing. I was wondering if these services, or any other cloud service for ...
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1answer
66 views

What does it mean to categories a feature as low-,mid-,high-level? [closed]

I primarily want to know, if you have been given a quantity/feature and it's characteristics then how will you classify that feature? What's the intuitive criteria? From vision POV it becomes a bit ...
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1answer
114 views

What algorithms are used for segmentation and classification of non solid regions in an image?

In the process of segmentation, pixels are assigned to regions based on features that distinguishes them from the rest of the image. Value Similarity and Spatial Proximity, for example, are two ...
5
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1answer
158 views

Is it feasible to train a Machine Learning Model (with image inputs) in an average personal computer?

There are lots of examples of machine learning systems that can recognize objects and extract other information from images with very high precision. To train the models of such systems is necessary (...
5
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1answer
700 views

Precise localization and characterization of rudimentary shapes with neural networks

I understand that there are flavors of (convolutional) neural networks that are useful for object localization and detection tasks of reasonable difficulty. In all of the examples I have seen so far, ...
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1answer
51 views

Can I limit the possible choices for a computer vision framework to recognize?

To risk giving away too much info, im building a piece of hardware with the job of identifying the object in front of it. If it can only be one of three different items, how can I tell the computer ...
3
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1answer
678 views

Image comparison algorithm, trying to figure out how similar two “binary” forms are

I'm a student I'm completely new to this technology maybe my approach could be completely wrong, I want to create an algorithm that compares the similarity between two binarized images. I'll explain: ...
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1answer
100 views

Can augmented reality be a training system for computer vision?

Is augmented reality a training system for computer vision? As in, Augmented systems use their data to help train computer vision algorithms, or is augmented reality computer vision itself?
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1answer
478 views

Why do action recognition algorithms perform better on ucf101dataset than HMDB51 dataset?

If we look at state of the art accuracy on the UCF101 data set, it is around 93% whereas for the HMDB51 data set it is around 66%. I looked at both the data sets and both contain videos of similar ...
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1answer
118 views

Use ConvNet to predict bitmap

I want to build a classifier which takes an aerial image and outputs a bitmap. The bitmap is supposed to be 1 at every pixel where the aerial image has water. For this process I want to use a ConvNet ...
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1answer
938 views

Are information processing rules from Gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
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3answers
3k views

When using neural networks to detect features in an image, how can locate that specific feature in the original image?

I understand how a neural network can be trained to recognise certain features in an image (faces, cars, ...), where the inputs are the image's pixels, and the output is a set of boolean values ...
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2answers
1k views

Do deep learning algorithms represent ensemble-based methods?

Shortly about deep learning (for reference): Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using a deep graph ...
4
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1answer
918 views

Applications of CNN for detecting crime from video surveillance cameras

Inspired by this discussion about recognizing human actions, I have found the Fall-Detection project which detects humans falling on the ground from a CCTV camera feed, and which can consider alerting ...
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1answer
218 views

How does Pinterest decipher what's on unmarked pictures and categorize them?

According to this article, Pinterest acquired VisualGraph, an image recognition and visual search technology startup. How does Pinterest apply VisualGraph technology for machine vision, image ...
4
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1answer
166 views

Why would neural network dream scenes mirror the hallucinations people experience when they're tripping?

In DeepDream wikipedia page it's suggested that a dreamlike images created by a convolutional neural network may be related to how visual cortex works in humans when they're tripping. The imagery ...
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10answers
5k views

How is it possible that deep neural networks are so easily fooled?

The following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g. How this is possible? Can you please ...

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