All Questions
580 questions
1
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1
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24
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How do neural scaling laws explain the improvements from LSTMs to Transformer based models
I was reading about a study on neural scaling laws from 2017 and they noted this as a summary. From Hestness, Joel; Narang, Sharan; Ardalani, Newsha; Diamos, Gregory; Jun, Heewoo; Kianinejad, Hassan; ...
- 279
0
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0
answers
37
views
When should you use a transformer and when LSTM, GRU and other Neural Networks?
There is a lot of information on the Internet that the transformer is better than RNN in everything, but is it true?
Examples:
«What if I need to translate words?»
«Generate text, images?»
«Play a ...
0
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0
answers
15
views
Neural Networks for LIDAR Images
I recently encountered this blog https://ouster.com/insights/blog/the-camera-is-in-the-lidar
It seems like one can leverage lidar data as an image quite nicely and therefore use 2D vision algorithms ...
- 101
0
votes
2
answers
55
views
Is there any actual difference between these 2 definitions of a state value function?
The definition of the value function in TRPO paper is
\begin{align}
V_\pi(s_t) &= \mathbb{E}_{a_t,s_{t+1},\ldots} \left[ \sum_{l=0}^{\infty} \gamma^l r(s_{t+l}) \right], \\[10pt]
a_t &\sim \pi(...
- 139
0
votes
0
answers
105
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Which computer vision model (or LLM) for segmentation?
I'm new here. I have nearly 2,000 bee images with hand annotations of masks of the full body. I want to automatically generate "head", "thorax" and "abdomen" from this ...
0
votes
1
answer
29
views
Is background segmentation effective for improving action recognition model on real-time human-object interaction videos?
I am working on an action recognition task involving human-object interactions using an I3D (3D CNN-based) model. The model was trained on pre-recorded videos, and it performed well during evaluation. ...
0
votes
0
answers
16
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How to 'induce' or 'teach' pretrained model to a continous Transformer token-pruning Algorithm
I am currently looking for ways to improve Transformers performance in image processing, especially in image segmentation. I found this paper by Kong, Z., et al called "SPViT: Enabling Faster ...
- 1
2
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0
answers
93
views
Indoor elements detect from floor image
I have a large collection of floor plans that I need to convert into indoor maps by extracting walls as lines, doors as lines, and rooms as polygons. Currently, I do this process manually.
The floor ...
- 71
0
votes
1
answer
108
views
Does Machine Learning focus on discriminative AI while Deep Learning also focus on generative AI?
I know that Deep Learning is subset of Machine learning
But is it correct that classical ML algorithms mainly focus on implementing Discriminative AI while DL algorithms implement both Generative AI ...
- 181
1
vote
0
answers
17
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Automatic Image Annotation Based On Colour
I need to annotate a large corpus of images for image segmentation.
I can generate this corpus of images myself and I can choose to color whatever needs to be annotated with a specific colour.
I would ...
- 47
0
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0
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84
views
How to fix segmentation model producing black segmentation masks?
Apologies in advance for incorrect formatting, I've been kindly sent here after posting my question on StackOverflow.
We're training a segmentation model using Snapchat's template for custom ...
1
vote
3
answers
428
views
Vision transformer for image segmentation
I am working with vision transformers (ViT) for the task of image segmentation, but I am unsure of which segmentation head to use.
I know I need a vision transformer as my backbone, and a segmentation ...
- 13
1
vote
0
answers
67
views
Visualization of Transposed Convolutions
After reading on Transposed Convolutions and Fully Convolutional Networks in the d2l book (14.10 and 14.11), I wondered about the visualization of transposed convolutions.
As you probably know, ...
- 153
0
votes
2
answers
107
views
What do we mean by "AI is correlated"?
From Wikipedia
Causal AI is a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation. One practical use for ...
- 117
0
votes
0
answers
34
views
why CAM does not use ReLU, unlike Grad-CAM?
I learned that Grad-CAM uses ReLU becuase it is only interested in positive incluence on the class of interest.
Then I think ReLU can also be used to CAM. But why they don't use ReLU?
- 13
0
votes
0
answers
1k
views
Uncensored auto-captioning libraries that work well for NSFW image datasets?
I have a large (>2.5 million files) dataset of NSFW images that I would like to auto-generate detailed (~100-150 token) captions for, using a visual language model similar to CogVLM or Llava.
I ...
0
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0
answers
41
views
Realtime cuboid vs cylinder classification of a 2D mask / object from a 3D scene?
Most realtime SOTA segmentation/detection model can reliably segment an object from a 2D input, and I can get the contours/polylines describing its edges in realtime. By realtime, I'll consider ...
0
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0
answers
57
views
Advice on Moving Object Segmentation with U-Net where the target is small
I have a problem I'm trying to solve. I'd like to spot a moving object in a video sequence. "Moving Object" is very vague, but it can be roughly defined as 'here is a bright point that seems ...
- 101
2
votes
2
answers
556
views
Is it easier to use back-propagation or genetic algorithms to teach an artificial intelligence?
I am making a very simple neural network for a school project, and I would like to know what the best and easiest way to "teach" a neural network would be. From what I know, backpropagation ...
- 23
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0
answers
21
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Are there leaderboards/tables/stats that compare inference times between close-sourced LLMs such as GPT 3.5/4 and Claude?
https://huggingface.co/spaces/optimum/llm-perf-leaderboard is great to compare inference times between LLMs but it misses close-sourced LLMs such as GPT 3.5/4 and Claude.
- 3,267
0
votes
1
answer
119
views
Image segmentation with noisy labels
I have a dataset which consists of satellite images and their labels which are indicated by let say class 1 and 2.
I want to perform image segmentation to detect pixels related to class 1 and 2. The ...
- 1
1
vote
2
answers
1k
views
What is the difference between densenet and resnet?
Is the only difference between the two how the skip connection is combined? Resnet combines skip connections through addition and Densenet through concatenating.
The Densenet paper appears to be ...
- 233
1
vote
1
answer
98
views
Is there any advantage of genetic algorithm (or programming) over Neural Networks? [closed]
I am planning to switch from neural networks to genetic algorithms (GA) and programming (GP).
One of the main hassles of working with neural networks is that it requires a large amount of training ...
- 339
0
votes
2
answers
61
views
Should I define my problem as image segmentation or detection?
I have a problem and have to decide wether it's an object detection or object segmentation problem. I want to use Yolov8 for training. We already have hundrets of images but they aren't labeled yet. ...
- 113
1
vote
1
answer
1k
views
When to use Pruning, Quantization , Distillation and others when optimizing speed
I want to understand how to optimize models for inference speed and am seeking some advice and best practices for the same.
I am a little bit aware of the concepts of pruning, quantization, and ...
- 789
4
votes
2
answers
3k
views
What are the differences between seq2seq and encoder-decoder architectures?
I've read many tutorials online that use both words interchangeably. When I search and find that they are the same, why not just use one word since they have the same definition?
user78615
1
vote
1
answer
133
views
Why are these two implementations of the $\epsilon$-greedy policy different?
According to the book Reinforcement Learning An Introduction, the epsilon greedy policy can generally implemented as:
$$
\pi(a|s) =
\begin{cases}
\frac{\epsilon}{|A|} + 1 - \epsilon & \text{if } ...
- 195
2
votes
1
answer
541
views
What are the similarities between Q-learning and Value Iteration?
This is the explanation of value iteration in our notes where you keep applying bellman optimality equation till it stops changing and then acting greedily wrt the value function gives the optimal ...
- 23
0
votes
1
answer
408
views
How to accurately detect grid cell boundaries in Python image processing?
I'm working on a Python algorithm to detect individual cells of a grid passed by an image. Currently, I'm facing an issue where the values inside each cell are being selected as contours along with ...
- 101
0
votes
1
answer
70
views
Binary instance segmentation - does the masks have to be complete
I am wondering if it is required or not that the masks used for binary instance segmentation are complete.
For instance, I want to find the buildings in aerial imagery. If my masks cover, let say ...
- 101
1
vote
1
answer
48
views
Is there validation data in K-fold cross-validation?
We know that in machine learning the dataset is divided into 3 parts: training data, validation data and test data.
On the other hand, K-fold cross-validation is defined as follows:
the dataset is ...
- 1,115
0
votes
1
answer
248
views
What is the difference between Machine Learning model, algorithm and hypothesis?
I'm fairly new to Machine Learning field and still to grasp the basics, so this question may seem very stupid, but what is the difference between Machine Learning model, algorithm and hypothesis?
Like ...
0
votes
1
answer
242
views
Image segmentation with varying resolution
I am looking to create a model that is able to perform binary segmentation of images with varying resolutions. For model should be able to classify tree or not tree regardless of the resolution of the ...
- 101
0
votes
1
answer
76
views
How to add engineered features to an image segmentation model
I have built a U-net model for image segmentation of 3-channel remote sensing images. I have a total of four classes; two of these classes look very similar and are hard to distinguish in the images ...
- 1
0
votes
1
answer
141
views
Which search algorithm expands nodes closest to the goal?
I want to know which search algorithm among A* and Best-First Search and Greedy First Search expands nodes closest to the goal. I have three opinions about A* and Best-First Search and Greedy First ...
- 3
0
votes
1
answer
170
views
What is the difference between A/B testing and Reinforcement Learning?
I was learning ML, and I learnt a new section called, Reinforcement Learning. After some research on web, I found that it is a trial and error technique by which ...
0
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0
answers
54
views
Batch Normalization Layer is not learning the data semantics of a dataset comprised of datasets from different sources
I have built a dataset for image segmentation that is comprised of datasets from several different sources.
Almost all of my models have problems with learning the correct parameters of the ...
- 125
0
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0
answers
320
views
Use AI/Computer Vision to detect scene changes
I'm trying to use AI and computer vision techniques to identify scene changes for a camera. Something like this:
What are some approaches to do this? Any ideas?
The scene is static. Somewhere I saw a ...
- 983
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votes
1
answer
38
views
Should I apply a min-max scale (range 0 to 1) before applying the normalisation or should I apply the z-score normalisation directly?
I want to implement a neural network in Pytorch for medical image segmentation. I should normalise my data.
Should I apply a min-max scale (range 0 to 1) before applying the normalisation or should I ...
- 101
0
votes
1
answer
192
views
How are the intuitions and mathematics of attention mechanisms related to those of PageRank?
Excuse me if you find this question too vague and not fitting to this forum and feel free to close it. The overall goal of my question is to get a better intuition of the attention concept and ...
4
votes
1
answer
291
views
How does Monte-Carlo Tree Search Compare to MCMC?
Monte-Carlo Tree Search was the method used for AlphaGo my understanding is: it would randomly search the state space of possible moves where the probability of choosing a move was proportional to the ...
- 454
2
votes
1
answer
215
views
How can I tell a CNN to ignore nodata values in satellite images?
I'm trying to train an image segmentation model on satellite images. There are two main issues: first, not all of the images are the same size. My understanding is that by using a fully convolutional ...
- 21
4
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1
answer
2k
views
What's the difference between GPT3.5 and InstructGPT?
I read about the different model series in GPT3.5 here - https://platform.openai.com/docs/models/gpt-3-5
At the beginning of the page, it mentions to look at https://platform.openai.com/docs/model-...
- 41
1
vote
1
answer
85
views
Are on-policy algorithms always better than off-policy ones?
I am studying RL and I have a question: Are on-policy algorithms always better than off-policy ones?
0
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1
answer
311
views
Should softmax be in the model or in the loss function?
Suppose I have an image segmentation model with an output of [ 128, 128, 2 ], segmenting an input image into 2 parts.
Commonly, loss functions have the sigmoid or ...
1
vote
0
answers
57
views
Creating border around specific areas of images
I have some 1000+ image, containing data like this
Red area: Symbols
Grey area: Text describing the symbol
Note: I draw these red/grey boxes just for visualization only.
Each symbol is unique in this ...
- 111
2
votes
0
answers
99
views
How does one deal with images that are too large to fit in the GPU memory for doing ML image analysis?
How does one deal with images that are too large to fit in the GPU memory for doing ML image analysis?
I am interested in detecting small structures on images which are themselves many GB in size. ...
- 121
1
vote
1
answer
96
views
How are these two equations for the optimal state-value function equivalent?
By substituting the optimal policy $\pi_{\star}$ into the Bellman equation, we get the Bellman equation for $v_{\pi_{\star}}(s)=v_{\star}(s)$:
$$ v_{\star}(s) = \sum\limits_a \pi_{\star}(a|s) \sum\...
- 1,115
3
votes
1
answer
589
views
Do the terms 'sample complexity' and 'sample efficiency' mean the same thing in RL context
For example, the the paper Soft Actor-Critic:Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor, both terms are mentioned but without explaining. I have seen them in other ...
- 195
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1
answer
4k
views
What's the difference between classification and segmentation in deep learning?
What's the difference between classification and segmentation in deep learning?
In particular, can the classification loss function be used for segmentation problems?
