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Questions tagged [object-recognition]

For questions about algorithms recognizing individual objects represented by any/all of their physical characteristics.

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How do map providers like Google calculate the distance between two coordinates and find turn by turn directions?

I have searched on how Google or any map provider calculates distance between two coordinates. The closest I could find is Haversine formula. If I draw a straight line between two points, then ...
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Double Convolution Layers in Yolov3

Lately, I have been working on yolov3 and have been trying to train it on x-ray images to detect a fracture. However, I have decided that I would want to increase the number of convolution layers for ...
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How to detect LEGO bricks by using a deep learning approach?

In my thesis I dealt with the question how a computer can recognize LEGO bricks. With multiple object detection, I chose a deep learning approach. I also looked at an existing training set of LEGO ...
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Detecting abnormalities in x-rays while taking into account demographics of a patient -automated

This is my first post so please forgive me for any mistakes. I am working on an object detection algorithm that can detect abnormalities in an x-ray. As a prototype, I will be using yolov3 (more ...
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YOLO v3 complete architecture

I am attempting to implement YOLO v3 in Tensorflow-Keras from scratch, with the aim of training my own model on a custom dataset. By that, I mean without using pretrained weights. I have gone through ...
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Consecutive frames can be discarded when training an SSD/YOLO?

Let's say I have a number of videos, and I want to train an SSD/YOLO (or FRCNN) to detect objects. In the case of a large amount of videos, there will be a lot of frames extracted and transferred to ...
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How do I detect similar objects in an image?

I want to tackle the problem of detecting similar objects in an image. To illustrate the problem consider this photo of some Lego bricks as my "input": The detection routine should identify similar ...
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Presence of object (highly occluded vehicle) in a scene

How to detect presence of object (highly occluded) in a scene? There are specific features (small patterns, etc), which allow to say that object is present, but it is not enough for detection for ...
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23 views

Having trouble understanding some of the details of R-CNN (first one)

Here is what I understand (what I think I understand). We first train out model on our images using transfer learning. So now we have a pre-trained model. For each image in out dataset, we compute ...
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156 views

Pseudocode for CNN with Bounding Box and Classifier

I've been looking at various bounding box algorithms, like the three versions of RCNN, SSD and YOLO, and I have noticed that not even the original papers include pseudocode for their algorithms. I ...
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95 views

Find object location (x, y) in an image

I am generating images that consist of points where the object's location is where the most overlap of points occurs. In this example, the object location is (25, 51). I am trying to train a model to ...
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A neural network for digits recognition doesn't work (MNIST, Numpy) [closed]

I'm a beginner in machine learning and I was trying to make a test neural network for digits recognition from scratch using Numpy. I used MNIST dataset for training and testing. Input layer have 28*28 ...
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Using batches in testing

If one examines SSD: Single Shot MultiBox Detector code from GitHub repository, it can be seen that, for a testing phase (evaluating network on test data set), there is a parameter ...
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120 views

What's the role of bounding boxes in object detection?

I'm quite new to the field of computer vision and was wondering what are the purposes of having the boundary boxes in object detection. Obviously, it shows where the detected object is, and using a ...
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Could AI understand what the number one is and detect it in our real world same as AI can recognize cars and other things?

I have a solid understanding what the numbers are. If I want, I can see numbers in everything. Could an AI have the same ability for any incoming information to tag them by numbers same as I have?
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How data augmentation like rotation affects the quality of detection?

I'm using an object detection neural network and I employ data augmentation to increase a little my small dataset. More specifically I do rotation, translation, mirroring and rescaling. I notice that ...
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665 views

Learning Rotated bounding box for object detection

I have checked out many methods and paper like yolo, ssd, etc with very promising result in detecting a rectangular box around object, But could not find any paper, which shows an learning a rotated ...
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258 views

When training an object detection network for one class, should I include empty images in the dataset?

I fine tuned MobileNetSSD for object detection using a dataset with just one class (~4000 images). All the training images include at least one bounding box related to that class (no empty images). By ...
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60 views

Recognition of small objects

I'm currently implementing an Android app for street sign recognition. My solution works quite well for the GTSRB dataset, since it provides a labeled test set of centered images. However, it doesn't ...
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How a game playing agent could identify potential objects and proximity?

Most implementations I'm seeing for playing games like Atari (usually similar to DeepMind's work using DQN) have 4 graphical frames of input fed into 3 convolutional layers which are then fed into a ...
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How to know whether the object is moving after it is being detected?

If my algorithm detects the type of object, how should I know if that object is moving or not? Suppose a person carrying an umbrella. How to know that the umbrella is moving? I am working on a ...
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62 views

What should a good loss curve look like?

This is a very basic question. I'm running a faster rcnn trainer on a dataset for object recognition. My images range from 200x200 to 7360x4912 in resolution. There are only 2 classes being trained (...
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Are there any pretrained models for human recognition from all angles?

I need to be able to detect and track humans from all angles, especially above. There are, obviously, quite a few well-studied models for human detection and tracking, usually as part of general-...
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What are the ways to calculate the error rate of a deep Convolutional Neural Network, when the network produces different results using the same data?

I am new to the object recognition community. Here I am asking about the broadly accepted ways to calculate the error rate of a deep CNN when the network produces different results using the same data....
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Keywords to describe people counting from a camera?

The subject matter is to count the number of people in a large room, wherein a camera is placed in a very high ceiling: an example would be Grand Central Station. Faces are not visible: the scalp (...
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233 views

Add training data to YOLO post-training

(Cross-posting here from the data science stack exchange, as my question didn't get any replies. I hope it's okay!) I've been playing around with YOLOv3 and obtaining some good results on the ~20 ...
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Can one use an Artificial Neural Network to determine the size of an object in a photograph?

My question relates to but doesn't duplicate a question that has been asked here. I've Googled a lot for an answer to the question: Can you find the dimensions of an object in a photo if you don't ...
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192 views

Simple Object Detection

I want to create a simple Object detection tool. So basically an Image will be provided to the tool and from that, it has to detect the number of objects. For eg An image of a dining table which ...
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1answer
156 views

Alternative to sliding window neural network (was: Object detect (or) image classification at specific locations in the frame)

Recent advances in Deeplearning and dedicated hardware has made it possible to detect images with a much better accuracy than ever. Neural networks are the gold standard for computer vision ...
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YOLO - How much is the position of the object relevant in learning?

I have the following question about You Only Look Once (YOLO) algorithm, for object recognition in CNNs. I have to develop a neural network to recognize web components in web applications - for ...
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95 views

How does the target output of a Single Shot Detector (SSD) look like?

According to the paper SSD: Single Shot MultiBox Detector, for each cell in a feature map k boxes are acquired and for each box we get $c$ class scores and $4$ offsets relative to the original default ...
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1answer
622 views

Training a CNN from scratch over COCO dataset

I am using Tensorflow Object Detection API for training a CNN from scratch on COCO dataset. I need to use this specific configuration. There is no pre-trained model on COCO with that configuration and ...
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91 views

How to label “other” while labeling image for object detection/classification?

I want to train a model to recognize different category of food (example: rice, burger, apple, pizza, orange,... ) After the first training, I realized that the model is detecting other object as ...
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390 views

How to label training data for YOLO

I am having a question on how to label training data for YOLO algorithm. Let's say that each label Y, we need to specify [Pc, bx, by, bh, bw], where Pc is the indicator for presence(1=present, 0=not ...
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508 views

Regarding Yolo and Keras

I'm trying to implement YOLO (tiny version, v1) into Keras framework. For the past two days, I've been relentlessly digging through Github and the likes in order to ...
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Object recognition by two or more traits that are orthogonal (informally speaking)

I would really appreciate if someone could comment the following method of training neural nets providing them with some meta data (Making them more color prone only if needed, whereas now they're ...
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Can translational invariance of CNNs be unwanted if object is likely in certain positions?

Various texts on using CNNs for object detection in images talk about how their translation invariance is a good thing. Which makes sense for tasks where the object could be anywhere in the image. Let'...
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Getting worse performance when training a pre-trained model with the existing class

I am training pre-trained SSD-InceptionV2-Coco to detect the "car", which is one of the classes in mscoco label. I train the model with ~50k sample from KITTI, 500k iteration with batch size 2. I ...
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FIlling space with empty bounding box

I'm detecting objects on images. I want to detect up to 10 objects, however, I'm not sure how to deal with the situation, where only one object is present. Should I fill the remaining spaces in the ...
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1answer
437 views

Understanding the loss function of You Only Look Once(YOLO) network

I'm trying to implement a custom version of YOLO neural network. Originally it was described in this paper. I have some problems understanding the loss function they used. Basic information: An ...
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1answer
126 views

Why does the classifier network in RPN output two scores?

The region proposal network (RPN) in Faster-RCNN models contains a classifier and a regressor network. Why does the classifier network output two scores (object and background) for each anchor instead ...
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Is understanding value for different features next step for object recognition?

Once the artificially intelligent machines are able to identify objects, we might want to teach them how to value different things differently based on their utility, demand, life, etc. How can we ...
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Transfer learning from model trained in a similar dataset

I am currently working on a defect detection algorithm but I only have a few samples of defects.I googled for defect detection datasets and I found this one: http://resources.mpi-inf.mpg.de/...
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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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660 views

Object detection in video

I have a video which is capture from a moving car and video showing plenty of details like pools, human, cars/buses, roads, etc, etc. The video I am playing in unity3d and camera Showing that video ...
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1answer
95 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 ...
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1answer
620 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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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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1answer
925 views

How to detect the empty parking spots?

I have some images of the empty parking as shown below. I 'd like to use deep learning to extract the parking spots. But in the beginning,am confused whether there are several ways to do the ...
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561 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, ...