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1answer
13 views

Is there any relationship between the batch size and the number of epochs?

I am currently running a program with a batch size of 17 instead of batch size 32. The benchmark results are obtained at a batch size of 32 with the number of epochs 700. Now I am running with batch ...
0
votes
1answer
8 views

How do you handle skewed image data?

I have an image data-set which I am training a CNN on. The Data-set is slightly skewed. So my solution up till now was to delete some images of the majority class. But I now realize that there are ...
0
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0answers
14 views

How general is generalization?

I am sorry but I have to explain my question using an example, I do not know how to ask it in proper scientific terms. Let's assume, I have trained a deep learning model on classifying hand gestures, ...
2
votes
1answer
14 views

Is it true that channels always represent colours of an image?

Convolutional neural networks are widely used in image-related tasks in artificial intelligence. The input of a conventional neural network is generally an image. The output of a convolutional neural ...
0
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0answers
9 views

Brain tumour detection using CNN

I have a fairly basic mathematical and implementational understanding of ML algorithms and CNNs, and I am trying to think of an approach for this task: https://www.kaggle.com/c/rsna-miccai-brain-tumor-...
0
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0answers
12 views

How to assess the goodness of a text generation algorithm

Take a RNN network fed with Shakespeare and generating Shakespeare-like text. Once a model seems mathematically fine, as can be assessed by observing its loss and accuracy over training epochs, how ...
0
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0answers
6 views

In a binary classification with CNNs features perform well by themselves, but performance degrades when features are used simultaneously for training

I am doing a binary classification with U-Net. When I use elevation as a feature to train my data the test set performs very well. When I use slope as a feature it performs really well. When I use ...
0
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0answers
11 views

Input and output data of digital twin (UAV)

Hi im a senior working with a team on a digital twin of a UAV. I will preface by saying that i just started learning about deep learning. My task is to build a neural network (2 layer feed forward ...
-1
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0answers
10 views

Estimate number of boxes on a pallet

Need to estimate number of boxes on the pallet. I have image from one viewpoint. Boxes can have different dimensions. They can be stacked on top of each other such that box dimensions don't exceed ...
1
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0answers
16 views

Mathematically speaking, Is it only the product operation used in the chain rule causing the vanishing or exploding gradient?

I am asking this question from the mathematical perspective of the vanishing and exploding gradient problems that we face generally during training deep neural networks. The chain rule of ...
-1
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0answers
9 views

How to find space utilised and free area in a room from Images

I have Multiple images of the room. How could I calculate space utilised and free space in the room from those images.
1
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0answers
13 views

How to handle Invalid actions for next state in Q-learning loss

I am implementing an RL application in an environment with illegal moves. For handling the illegal moves I am currently just picking an action as the maximum Q-value from the set of legal Q-values. So ...
0
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0answers
9 views

Counting number of coaches in a train from real time video feed

I have a real time video feed of a train platform. I was able to detect coaches using CNN based model. But how can I calculate number of coaches in the train that passed the platform as well as the ...
0
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0answers
4 views

Data Augmentation for Object Detection - Polygon Region Shape

I'm looking to run a Mask RCNN code on my dataset of about 2700 images. The images are too large and I would like to resize them, and I would also like to add some shear, scale and zoom augmentations. ...
0
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1answer
32 views

Can a Reinforcement Learning problem with multiple simultaneous actions be formalized as a Multiagent Partially Observable Markov Decision Process?

Consider the following decision making problem. We have a controller that selects locations from a grid of coordinates and captures an image (observation $o_t$) with a camera at each location (action $...
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0answers
8 views

proof of convergence for the random forest algorithm

I am looking for the proof of convergence of the random forest algorithm. A cursory google search shows many, but I do not understand which version (original?) of the algorithm this is. Can you kindly ...
0
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0answers
31 views

Need help for question 2 [closed]

I am doing on one of my homework assignment and I am not sure on how to do question 2 as I do not quite understand the concept of how to construct using decision tree based on the data shown. I have ...
0
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0answers
10 views

Usecases where pretrained models are used without retraining

I was starting out with deep learning and come across a lot of pretrained models in frameworks and sites such as tensorflow model zoo. Are these models actually used by other developers in real use ...
0
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1answer
22 views

What is meant by "shorter connections" in the case of deep convolutional neural networks?

Consider the following two excerpts from the research paper titled Densely Connected Convolutional Networks by Gao Huang et al. #1: From abstract Recent work has shown that convolutional networks can ...
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0answers
11 views

How to Train Big Size Image and Predict Various Size of Images

I don't have deep knowledge of the neural network, but I would like to segment the road from UAV images and detect cracks on them. My first question: I am planning to do fine-tuning from pre-trained ...
1
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0answers
17 views

Reinforcement Learning for Finite Time Horizon and Non-Trivial Terminal Reward

I notice that most Deep Reinforcement Learning (DRL) works focus on Markov Decision Process (MDP) with an infinite time horizon. Are there any algorithms that work well on finite MDP and non-trivial ...
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0answers
25 views

Is this a good implementation of this LSTM architecture?

I had been looking at some OCR problems and came across this presentation. I implemented it. In the presentation, there is the LSTM-Stack (diagram and algorithm, slide 32): Here is a visualization of ...
5
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3answers
645 views

Is it okay to use publicly available Instagram videos to train an AI?

Since I haven't found any good training data for my university project, I want to use pictures and videos from public Instagram profiles. Am I allowed to do that?
1
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2answers
80 views

How to measure Deep RL algorithms in terms of safety?

I applied for a Ph.D. in AI, my advisor told me that my thesis is about safe applications of deep RL algorithms in healthcare. So I decided to do as the first paper, a comparison of Deep RL algorithms ...
0
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0answers
16 views

How Long Can BPTT Truncated?

I wanted to ask what is, in general, the maximum value (the order of magnitude) of the number of time steps I can back-propagate in the past using TBTT (Truncated Backpropagation Through Time) in an ...
0
votes
1answer
12 views

How to reduce the number of clusters produced by the Markov Clustering Algorithm?

I have used the Markov Clustering Algorithm (MCL) to cluster tweets, based on their similarity. However, I got a too high number of clusters, and most of the clusters have only one tweet. Any ...
0
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0answers
24 views

What all are the known reasons for the decline in the performance of a neural network if we keep on increasing the depth of it?

Progress in many application tasks in artificial intelligence is achieved by increasing the depth of the neural networks. But if we keep on increasing the number of layers in the neural network, the ...
0
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0answers
22 views

Changing order of backpropagation training set

I'm training a simple feedforward network to model the XOR truth table. So far, I can get the network to converge to the solution quite quickly if the training input is always the same. For instance: ...
1
vote
1answer
28 views

Is "width of a neural network" a wrong phrase?

Depth of the neural network is equal to the total number of layers in the neural network except input layer. so, neural network with more number of layers are called deep neural networks. Width, in ...
0
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0answers
11 views

How does the margin classifier lower the generalization error?

I am a beginner in machine learning, and I started learning about machine learning starting from linear classification. I am currently reading about margin classifier, and even though i understand the ...
-1
votes
1answer
57 views

Would empathy in AI be a reliable tool/capacity, or contribute to a solution to avoid harm done to humans or to other versions of AI?

INTRODUCTION: I am not a developer, scientist, or expert in anything related to AI. Just a random person who happens to be curious about AI and science in general. So please be so kind as to forgive ...
0
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0answers
15 views

multi agent deep deterministic policy gradient for discrete actions

I am solving a multi agent problem where each agent has a critic and actor. The problem I am solving has discrete actions and discrete states. I came cross multi-agent deep deterministic policy ...
0
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0answers
7 views

Loss & accuracy curves from learning rate range test interpretation

I am working on a project doing experiments with the Learning Rate Range Test (See "A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and ...
0
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0answers
16 views

Multiple GRU layers to improve a text generation

I am using the model in this colab https://colab.research.google.com/github/tensorflow/text/blob/master/docs/tutorials/text_generation.ipynb#scrollTo=AM2Uma_-yVIq for Shakespeare like text generation. ...
0
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0answers
29 views

Why do some of the algorithms take some extra space around the actual bounding box?

In some of the algorithms, there is a need to crop the object in an image. So, bounding boxes need to be used in order to crop the image to contain object only. Bounding boxes provide the information ...
0
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0answers
10 views

Identify Merchants from Transaction Dataset

I have a transaction dataset, each transaction is in an unstructured format. The objective is to identify merchant from each transaction. If we look it from NER point of view, there would be problem ...
0
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1answer
54 views
+50

Why is the validation accuracy lower in case of CNN?

I fed the same set of 1.4 million data to two different models: MLP CNN model In both cases, I used the same parameters and hyperparameters. The CNN is showing comparatively lower accuracy (80%) ...
0
votes
1answer
24 views

How to understand the common practices followed for writing a "bounding box" for an image in datasets?

For the image datasets, there may be a bounding box for each image at the dataset. It is an annotation for an image. It is a rectangular box intended for focusing on something inside the image. I read ...
-1
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0answers
25 views

How to write a Proof-Of-Concept(POC) for machine learning model?

I've found that If any company is interested in your product, But they don't know it will fit, it will work or they don't trust you, They will ask you for a POC or Proof-Of-concept I need to write a ...
2
votes
1answer
66 views

How to generate a response while considering past questions as well?

User: What is the tallest mountain? Agent: Everest User: Where is it located? # Agent hears: "Where is Everest located?" Agent: Nepal I want to be able ...
0
votes
1answer
25 views

How to show $\rho > 0$ when $\rho$ be minimum attainable from $y_n(W^{*T}X_n)$, where $W^*$ the vector that separates the data?

In the book Learning from Data written (by Abu Mostafa), we have the following exercise: Let $\rho$ be minimum attainable from $y_n(W^{*T}X_n)$ where $W^*$ is the vector that separates the data. Show ...
0
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0answers
27 views

Uniform representation of images for machine learning

I'm new to the field of ML so please bear with me while I try to explain what I'm looking for. In most machine learning pipelines that deal with images there is a requirement to "normalize" ...
1
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0answers
10 views

What is the reason behind using node embeddings?

I was reading Chapter 3 from the following book (here) on graph representation learning. The chapter is about node embeddings. Question: What is the point of using node embeddings? Do we use them: to ...
1
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0answers
10 views

What are examples of node 'features' in graph networks?

Context: I was reading Chapter 3 in the following book (here) about graph representation learning. Before I get to node embeddings, I wanted to make sure that I do understand what is meant by the ...
0
votes
1answer
22 views

How to handle random order of inputs and get same output?

I am a beginner with DL. I did some tutorials and I know the basics of TensorFlow. But I have a problem understanding how to construct more advanced NNs. Let's say I have 6 inputs and a list of 500 ...
1
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0answers
28 views
0
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0answers
5 views

Do the output of RNN individual layers go through Softmax when going from one layer to the next in a stacked RNN (many to one architecture)?

In most of the online materials that I've read, the equations of RNNs are shown only for a single layer RNN with the output going through softmax (for a many-to-one architecture). I am trying to find ...
3
votes
1answer
43 views

In reinforcement learning, why are policies defined as functions of states and not observations?

I am new to RL and I am following Sutton & Barto's book. My doubt is, when we talk about the policy of our agent, we say it is the probability of taking some action $a$ given the state $s$. ...
0
votes
0answers
17 views

In anchor based object detection, why don't the anchors share the same weights?

After reading about YOLO V3 and Faster R-CNN, I don't understand why the weights for the regression head aren't the same across all boxes of the same size. Given that the backbone of these systems is ...
0
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0answers
8 views

Can I perform 3D point cloud per-point labeling from binary classification alone?

All, It seems that the process of individually labeling points in 3D point clouds is no small task. I believe that's why tools like these exist: Sagemaker Pointly But ... what if there are only two ...

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