# Tag Info

Accepted

### Would Google's self-driving-car stop when it sees somebody with a T-shirt with a stop sign printed on it?

Google’s self-driving car most likely uses mapping of traffic signs using google street view images for roadway inventory management. If traffic signs are not in its database, it can still “see” and ...
• 10k
Accepted

### What will happen when you place a fake speedsign on a highway?

https://www.technologyreview.com/s/530276/hidden-obstacles-for-googles-self-driving-cars/ Google’s cars can detect and respond to stop signs that aren't on its map, a feature that was introduced to ...
• 249

### How to detect LEGO bricks by using a deep learning approach?

So I am assuming that you are trying to detect a lego brick from the image. One idea is that you can use transfer learning. Leveraging a pre-trained machine learning model is called transfer learning. ...

### What could an oscillating training loss curve represent?

Try lowering the learning rate. Such a loss curve can be indicative of a high learning rate. Due to a high learning rate the algorithm can take large steps in the direction of the gradient and miss ...

### What could an oscillating training loss curve represent?

Overview As it has already been observed, your main problem, beside the training related issues like fixing the learning rate, is you have basically no chance to learn such a big model woth such a ...
Accepted

### Small size datasets for object detection, segmentation and localization

There are various dataset available such as Pascal VOC dataset: You can perform all your task with these. size of the dataset is as follows ADE20K Semantic Segmentation Dataset: you can perform ...
• 328
Accepted

### How can I develop an object detection system that counts the number of objects and determines their position in an image?

If you want to get experience, you should probably start with some easier task. Object detection and localization are relatively hard and writing a neural network and image processing pipeline from ...
• 333

### Can one use an Artificial Neural Network to determine the size of an object in a photograph?

In my thesis I actually solve the problem of depth estimation with a CNN based on a single monocular image so I can share my experiences for understanding that problem. As you already stated in ...

### Can one use an Artificial Neural Network to determine the size of an object in a photograph?

Can one use an Artificial Neural Network to determine the size of an object in a photograph? Yes: Learning Depth from Single Monocular Images In the end, depth is just one special form of size. Of ...
• 1,007

### Can translational invariance of CNNs be unwanted if object is likely in certain positions?

According to your example: Trees will likely be in the bottom half of the image. Still, you will not know whether there will be one, two or five trees. Thanks to translation invariance property of ...
• 333
Accepted

### Why does the classifier network in RPN output two scores?

I just want to provide this intuition this NN consists of a 2 steps detection pipeline (the region proposal and regression + classification in parallel) exploring a certain range of scales and ...
Accepted

### How does Google's self-driving car identify pedestrians?

The AI of the car uses sensor data to process all the data and classifies objects based on the size, shape and movement patterns. It can recognize surroundings from a 360 degree perspective by making ...
• 10k
Accepted

### Is there any computer vision technology that can detect any type of object?

TL;DR This is possible. You need a correctly labeled dataset. Your dataset has two labels: $y\in \{\text{background},\text{object in frame}\}$ or simply $y\in \{0,1\}$ This labelling avoids ...
• 1,016

### What would the commercial application of a conscious AI look like/be?

They may be just for fun. If you had a robot that understood you, could hold a conversation with you about your interests, and even had goals of its own (good or bad), it wouldn't really need to do ...
• 21

### What are some techniques/method that can be used to train and detect objects like cars and humans?

The terms you are looking for are deeplearning and convolutional neural networks for object detection. Google responds well to these terms. From academical point of view you can start from: Single ...
• 341

### How to detect the empty parking spots?

Object detection is a regression of the bounding box (rectangle) around the object. In this way, the two ways you suggest are equivalent. What I suggest you to look at is lane detection for self-...
• 1,877

### Precise localization and characterization of rudimentary shapes with neural networks

I think you're describing "object localization and detection" which combines object identification with discovery of its spatial placement in the field of view. There's been a lot of work on this in ...
• 671
Accepted

### What is the difference between pixel-based object recognition and feature-based object recognition?

Pixel based object recognition, like the name says, works by analyzing the individual pixels of an image. For example: You analyze an image with a lot of different shades of blue and some grey pixels -...
• 1,644

### Keywords to describe people counting from a camera?

I usually start with some papers and look at the references: Counting people using video cameras Sheng-Fuu Lin, Jaw-Yeh Chen, Hung-Xin Chao, Estimation of Number of People in Crowded Scenes Using ...
• 1,007
Accepted

### How to label training data for YOLO

In effect, the midpoint is contained in cell $2$. Cells $1,3,4$ will be shown at $P_c=0$ according to the YOLO algorithm, which only takes in count the cell that contains the midpoint and calculates ...
• 76
Accepted

### Which API can I use for tracking the position of animal in one or more images?

FastAI is the most “out of the box” API for this type of task. For video examples (and a little theory) check out the MOOC section of their site. Practical Deep Learning and Cutting Edge Deep ...
• 499

### What could an oscillating training loss curve represent?

Nicola Bernini's answer is quite comprehensive. Here are my insights. First of all, think whether you really need neural networks to solve your problem. Think whether traditional computer vision ...
• 71

### Are there deep networks that can differentiate object class from individual object?

In this case, you have an ontology and want to learn the ontology. There are many researches in this topic that you can find. However, the data could be the most challenging part. Some of the ...
• 1,663

### Is it possible to train a CNN to predict the dimensions of primitive objects from point clouds?

I'm working on a similar problem. I'm using a 2D point cloud of an object, for example, X and Y coordinates for height, and with that more simple data set I will train a regression model (currently ...

### Is it possible to use AI for detecting the volume of a cup

This could be possible, providing you have the right dataset to train it on. The volume of a cup consist of width, height and depth. You can probably detect all three of those given the bounding box ...
• 1,715
1 vote

### Which model should I use to find (only) the object location (in terms of coordinates) in an image?

What is a good model for this objective? I will try to give another perspective: Solve it without machine learning model Your problem is try to find the most overlapping point. If the image above is ...
• 2,551
1 vote
Accepted

### A neural network for digits recognition doesn't work (MNIST, Numpy)

It seems I've solved the issue. There was several mistakes: 1. I've generated random weights from 0 to 1. As a result, too big numbers passed through softmax function (>10000), and the function wasn't ...
1 vote
Accepted

### How data augmentation like rotation affects the quality of detection?

The problem is that this kind of data augmentation seems (in theory) to hamper the network to gain precision on bounding boxes location as it loosens the frame. Yes, it is clear from your examples ...
• 9,369

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