All Questions
Tagged with neural-network computer-vision
76 questions
0
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0
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8
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Should I interleave sin and cosine in sinusoidal positional encoding?
I'm trying to implement a sinusoidal positional encoding. I found two solutions that give different encodings. I am wondering if one of them is wrong or both are correct. I showcase visual figures of ...
- 101
0
votes
1
answer
26
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What is the "fast version" of ZFNet referenced in SPPNet and Faster R-CNN papers?
I'm reading old papers:
SPPNet: Link
Faster R-CNN: Link
In both cases, the authors refer to a "fast version of Zeiler and Fergus (ZF) Net"; specifically:
In SPPNet:
ZF-5: this ...
0
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0
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36
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Losing Information while resizing the image in Segmentation task using U-net
I'm using U-net architecture to build a segmentation task of image. During training I have image of size 256256 image. It works very well on the segmentation of same size 256256 or near to size 256*...
0
votes
1
answer
60
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How do I ensure final output shape matches input shape for a semantic segmentation task?
I trying to replicate the semantic segmentation example
https://keras.io/examples/vision/oxford_pets_image_segmentation/
but train on my own data. I have 8 labels (7 features + background). My images ...
2
votes
1
answer
414
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Is vision transformer (ViT) always better than CNN?
The paper - AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE proposed vision transformer and outperformed CNN-based models in many cases.
When it comes to sequential data, we ...
- 23
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1
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66
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Classification: ClassA vs. "everything else"
I am trying to create a neural network for recognizing a particular object. Maybe I am approaching this task from the wrong side, but, in my mind, this task boils down to teaching the network to do a ...
- 121
1
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0
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25
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Suggestions for labeling regression data to improve model accuracy
I'm working on a convolutional neural network that should predict up to 3 (x,y) coordinate pairs representing the waypoints of a concrete path, given an input image. This network will be used to help ...
- 11
0
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1
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95
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How to handle the case of multiple ground truth boxes having high IOU with the same predicted box?
In single shot detector the matching strategy between ground truth and predicted box starts with the following step:
For each ground truth box we are selecting from default boxes that vary over ...
- 231
0
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1
answer
1k
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What is `Multi-scale` in Multiscale Convolutional Network?
I was reading an article on Deep Learning and came across this term called Multi-scale Neural Network. I fully understand the concepts of convolutional neural network but it is a bit difficult to ...
- 103
1
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0
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22
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Attention mechanism: Why apply multiple different transformations to obtain query, key, value
I have two questions about the structure of attention modules:
Since I work with imagery I will be talking about using convolutions on feature maps in order to obtain attention maps.
If we have a set ...
- 181
3
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2
answers
1k
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Less parameters - in general within ResNets
My question is about the parameters of the ResNet.
Why does the network tend to have fewer parameters than the VGG? This would be the case if I got the paper and the summary from
Yannic Kilcher ...
- 31
0
votes
1
answer
210
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Training the network with some batch size - code
There is my "training" code below, I wrote it based on one youtube tutorial. I don't understand actually one part: batch_X = train_X[i:i+BATCH_SIZE], batch_y = train_y[i:i+BATCH_SIZE]. How ...
- 149
1
vote
1
answer
361
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Feature extraction from sequence of images with Siamese Neural Network
I am trying to train a neural network to recognize certain actions in short movies.
Each such movie consists of a fixed number of frames, each frame - the image is of course the same size, after ...
- 113
1
vote
0
answers
23
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Machine learning model (neural network or SVM) for unequal feature matrices size
I have feature matrices obtained from visual bags of words model for various dictionary sizes. Example, Nx5, Nx10, …., Nx15000. Where N is the number of samples and 5, 10, …15000 are the visual ...
- 11
1
vote
1
answer
364
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Why are axes-aligned bounding boxes used in object detection
I understand (I think) why in object detection, the result is a rectangle:
it is a simple shape that can be defined by 4 variables (2 pairs coords of opposite corners or 1 pair of coords + width and ...
- 205
1
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0
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65
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Denoising Prior to Image Classification
From what I have read, Denoising during preprocessing for image classification tasks seems to be a bit controversial.
While on one hand it might improve classification accuracy, the computational ...
- 123
1
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0
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136
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What should be the best CNN model for Feature extraction of images for Image-Image search engine using LSH?
I have images something like the below:
And like this:
I have a huge data around 20M or so am I want to apply de-duplication and improve the search for this ...
- 323
0
votes
1
answer
55
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How to manage memory constraint and increase speed for 1 vs rest image similarity comparison for over 100k images for computer vision?
I'm looking for ideas on how to do things in a better way, efficiently when using Machine/Deep Learning.
I am working on a search improvement problem using Computer vision where I am thinking about ...
- 323
1
vote
1
answer
41
views
Creating new images [closed]
I would like to create new images of landscapes with deep neural network. If my input is a large dataset of pictures of landscapes, how can I do to output new pictures of landscapes ? Which techniques ...
- 11
1
vote
0
answers
17
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Can convolutional network learn structural properties of one feature w.r.t to other?
I'm going through the literature on pose-estimation ( DeeperCut, OpenPose, MultiPersonPosetrack).
I'm interested in knowing whether these networks/ generally a CNN can learn properties (geometrical) ...
5
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1
answer
4k
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Which is the "BEST" deep learning model for "Custom" object detection for images & real time. YOLO v3, v4, v5, EfficientDet?
Whenever I look for object detection model, I find YOLO v3 most of the times and that might be due to the fact that it is the last version created by original ...
- 323
0
votes
1
answer
169
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Cable angle measurement (rotation)
I need to detect the rotation of a cable (degree) in the x-axis with high precision [0.2 (or more) degree detection] from its original state.
Detailed description:
I have a cable that is set in its ...
- 61
1
vote
1
answer
325
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Building a prediction model for dynamic coordinates and later categorize as binary classification
Project Summary
I have a website (academic project) that records mouse movements such as click, mouse up, mouse down, etc. It records the coordinates for each event on a given web page from a visitor....
0
votes
1
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240
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the size of training data set in the context of computer vision
Generally speaking, for training a machine learning model, the size of training data set should be bigger than the number of predictors. For a neural network, or even a deep learning model, the number ...
- 157
0
votes
1
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736
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UNet Model accuracy is stuck at exact 0.5 (neither more or less) (No class imbalance, tried tuning learning rate)
This is using PyTorch
I have been trying to implement UNet model on my images, however, my model accuracy is always exact 0.5. Loss does decrease.
I have also checked for class imbalance. I have ...
- 103
3
votes
1
answer
585
views
EfficientNet: Compound scaling method intuition
I was reading the paper EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks and couldn't get my head around this sentence:
Intuitively, the compound scaling method makes sense ...
3
votes
0
answers
65
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Information Extraction from image / text - approach?
I need assistance with a ML project I am currently trying to create.
I receive a lot of invoices from a lot of different suppliers - all in their own unique layout. I need to extract 3 key elements ...
- 185
2
votes
3
answers
381
views
Can the same CNN architecture be used for different data sets?
I have a CNN architecture that works well on 32x32x3 images. Can I use that same architecture for a data set made up of 28x28x1 images? (Both data sets have 10 classes). If this is possible, what ...
- 21
-1
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3
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3k
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why the sigmoid function will be 1 and 0 if we use a fully connected layer that produce a big enough positive(res negative )output
HI I am using a fully connected network that uses sigmoid if we feed a a big enough weights the sigmoid function will finally become 1 or 0 , is there any solution to avoid this ?
and will this lead ...
- 387
1
vote
1
answer
47
views
Reconize a card from a video stream
I want to make an mobile app where you scan using the camera and it gives you the card you just scanned. (from a board game)
I got a PNG of each and every single existing cards, but I don't really ...
- 11
6
votes
1
answer
64
views
Unable to understand the meaning of following lines of the research paper for image segmentation
I am implementing a paper on image segmentation. It is based on the slight modification of the u-net architecture.
The paper is based on encoder and decoder steps
Following are the lines of the paper ...
- 148
0
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1
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38
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Is text recognition by definition a part of image recognition?
I'm referring to more advanced text recognition systems that are using neural networks to find and extract text from images like the ones Google and Microsoft are offering on their ML platforms.
If ...
- 3
3
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0
answers
983
views
How to calculate Average Precision for Image Segmentation?
If I've understood things correctly, when calculating AP for Object Detection (e.g. VOC, COCO etc) the procedure is:
collect up all the detected objects in your dataset
sort the detections by their ...
- 131
3
votes
1
answer
7k
views
What is Coarse-to-Fine in the context of neural networks?
I read in many paper that mentions coarse-to-fine as a technique in deep learning, but I could never figure what exactly they mean. Is it related to multiscale inference, where they use coarse and ...
- 133
2
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2
answers
1k
views
Equivariance vs Invariance in Convolutional Neural Networks
Could someone please explain to me in details (possibly from mathematical point of view) what is the role of Equivariance and Invariance in Convolutional Neural Networks, and how are they actually ...
- 746
1
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0
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869
views
Examples for multi-input Convolutional Neural Network
I want to create a multi inputs Convolutional Neural Network (cnn) that takes two inputs and produces one output of the inputs class by using Keras. I searched for resources that explain multi inputs ...
- 2,015
2
votes
1
answer
4k
views
How to visualize image segmentation results
I am using u-net to do semantic segmentation for N>1 classes. The input size is (128,128,3), the output size will be (128,128,N). what is the correct way see the prediction as an image ot size n1 x n2 ...
- 579
1
vote
1
answer
77
views
What exactly does the model generation mean in this diagram?
I've been trying to grasp a research paper on image colorization using neural networks here I am stuck at this diagram. What I need help on, is the Model Generation step after Feature extraction. ...
- 13
2
votes
2
answers
4k
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How to properly save and load an intermediate model in Keras?
I'm working with a model that involves 3 stages of 'nesting' of models in Keras.
Conceptually the first is a transfer learning CNN model, for example MobileNetV2. (Model 1) This is then wrapped by a ...
8
votes
2
answers
183
views
Neural Network Architecture for Identifying Image Copies
I have a large image collection and wish to identify the images within that collection that appear to copy other images from the collection.
To give you a sense of the kinds of image pairs that I ...
- 204
5
votes
1
answer
3k
views
How design a autoencoder architecture
I would like to build an autoencoder (CNN) to learn a representation of my data.
I never built such a network and I have some experience in supervised learning (classification).
I would like to know ...
- 428
2
votes
0
answers
283
views
Maximum number of classes YOLO net can recognize on mobile
I'm trying to make a mobile app on image recognition(Computer Vision Application) . Does anyone know whether modern day smartphones have enough processing power/memory to recognize, say about 1 ...
3
votes
2
answers
219
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 example
An image of a dining table ...
- 131
3
votes
1
answer
277
views
How to label "other" while labeling image for object detection/classification?
I want to train a model to recognize the different categories of food e.g. rice, burger, apple, pizza, orange and other things.
After the first training, I realized that the model is detecting other ...
- 141
4
votes
0
answers
449
views
Spatial Transformer Networks and Data Augmentation
We are all familiar with the famous Deep Mind paper STN.
Upon implementation, such as here, did anyone still use input data augementation such as affine transformations?
There are used to make CNN ...
- 273
13
votes
1
answer
9k
views
What is difference between Fully Connected layer and Bilinear layer in CNN?
What is the difference between Fully Connected layers and Bilinear layers in deep learning?
- 2,015
3
votes
1
answer
5k
views
How to convert night image to day image?
I have set of night images which I will be using for self driving. But I want to convert those images into day images. I have developed algorithm based on day image but it is not good for night images ...
- 87
3
votes
3
answers
1k
views
The goal of fine tuning
I would like to ask what is the goal of fine-tuning a VGGNet on my dataset.
What does fine-tuning mean? Does it mean to change the weights or keep the weight values?
- 2,015
3
votes
2
answers
2k
views
Watermark detection using Deep Learning [closed]
I have images with and without watermark. There is only one type of watermark. I have tried VGG16 transfer learning, but results were bad.
What are the methods to ...
- 59
1
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0
answers
88
views
How to estimate Distance to Obstacles using Lidar's BEV(Bir's Eye view ) Representation?
I am using a implementation that use both camera and Lidar for 3D obstacle detection for self driving cars but I have no idea how to calculate the distance to the obstacles since the Lidar uses the ...
- 387