Questions tagged [transfer-learning]

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Comparison with transfer learning and CNN from scratch on a small dataset

I am doing image classification with CNN, and I have a training set of 3200 imges and a training set of 400 images. I have used two different approches for doing this classification : Transfer ...
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16 views

Training of a CNN stops at the seventh epoch

I am doing image classification, and I am using transfer learning to do this. My problem is that if I build the network, and then I train it, the training process stops at the seventh epoch, even if I ...
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11 views

Model not learning when using transfer learning

I am working on a personal project on image classification (two classes) and am trying to see how the MobileNet v2 structure would perform. While training the training accuracy is already quite high ...
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4answers
23 views

Image Classification using Single Class Dataset using Transfer Learning [closed]

I only have around 1000 images of vehicle. I need to train a model that can identify if the image is vehicle or not-vehicle. I do not have a dataset for not-vehicle, as it could be anything besides ...
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1answer
13 views

Transfer learning between Language Model and classification

Following this fast.ai lecture, I am trying to understand the mechanism of Transfer Learning in NLP from a general Language Model (LM) to a classification problem. What is exactly taken from the ...
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1answer
45 views

Why/When should I use VGG16 to do fine-tuning? [closed]

Why or When should I use VGG16 in my cnn? what is the pros and cons to use this model? I search but not found this answer. If you have references, I appreciate
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34 views

Accuracy of CNN on images taken under different conditions

I have a dataset containing images taken under 4 different conditions. When training the model, I use the same proportion of images (25%) from each condition. Then, I'm testing on 4 different test ...
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11 views

Transfer learning training accuracy starts from a fixed value

I am training a transfer learning model using tensorflow.keras library for image classification. I am dealing with 7 classes. I have used several pre-trained models ...
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95 views

How to use additional variables that are not available in test set?

I have additional variables in my dataset that are somewhat correlated to the continuous target variable, but that are completely unavailable in the test set. So, I'm wondering how the best to use ...
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1answer
36 views

How to fine tuning VGG16 with my own layers

I want to maintain the first 4 layers of vgg 16 and add the last layer. I have this example: ...
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16 views

How to apply transfer learning on a regression problem?

I am working on predicting mechanical failures and I have trained a model to predict when a component will fail on what type of machine. I would like to now use this prediction model to predict the ...
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1answer
16 views

Transfer learning VGG16 does not work as expected. (Detect tacos as hamburgers)

I am new in this field of machine learning, to test I wanted to do a simple project. Create a cnn capable of recognizing hamburger images. As I do not have the ability to collect more than 10,000 ...
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24 views

ResNet50 Model is not learning with transfer learning in keras

I am trying to perform transfer learning on ResNet50 model pretrained on Imagenet weights for PASCAL VOC 2012 dataset. As it is a multi label dataset, I am using ...
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1answer
24 views

Can I save only some VGG19's layers into a .H5 file?

I am training a deep-learning style transfer model with the pretrained-VGG19 CNN. My aim is to use it in my Android app for personal purposes with Google Firebase Machine Learning Kit (which would ...
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18 views

Transfer Learning and Recommender Systems

I have a task in which I am pretending to have an "unobserved" system, let's call it the target system, that I am using an LSTM from a similar system that has observations to perform the regression. I ...
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1answer
46 views

Smallest Possible Dataset for Text Classification using BERT

What are your experiences for appropriate dataset sizes for usual text classification tasks using a finetuned BERT such as sentiment analysis? ~100 examples ~1000 examples ... ~10000000 examples ...
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1answer
8 views

layers of transfer learning

The disadvantage of using transfer learning is that it cannot be layered to reduce the number of parameters. In that statement what are the layers of transfer learning and the number of parameters?
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133 views

incremental learning vs transfer learning

Can anyone explain me how incremental learning differs from transfer learning with example? Also does Transfer learning limited to neural networks?
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1answer
18 views

Hybrid classification neural network

I have product data and I need to classify products to categories (for example Lenovo laptop to Laptops category, etc.), each product has properties such as: description list with image URLs (...
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24 views

How to do transfer learning with limited data

I'm working on point cloud classification problem. I'm building a NN to classify point cloud. I found a really nice architecture that I want to use, called point net that receive a set of ordered ...
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1answer
123 views

How to add a new category to a existing trained deep learning model?

i have trained my deep learning model initially with 5 classes now i want to add another class without training the whole model over again for those 5 classes. How can I do that?
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1answer
20 views

Using data agumentation for a frozen pre-trained model

I was following the following article with regards to doing transfer learning: https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html In the section, Using ...
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20 views

Fine-Tuning VGG16 : how to get features maps of training examples before fully-connected layers

I am working on a classification problem in a project. The specificity of my problem is that I have to use two different type of data to manage it. My classes are Car, Pedestrian, Truck and Cyclist. ...
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1answer
107 views

Are mainstream pre-trained models useful as discriminators?

In the context of GANs I see many papers designing new discriminator networks. I'm curious about the usefulness of designing discriminators as modified versions of mainstream models like Inception, ...
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28 views

using dataset to classifying and labelling another unlabeded dataset

I collect a collection of posts from Facebook and I use a published sentiment datset to labeling my collected dataset. is this a right technique and what its name is this transfer-learning ?
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1answer
181 views

Transfer learning VGGish (AudioSet). Impact of zero padding to fit the input size

I am trying to train a network on top of the VGGish architecture (https://github.com/tensorflow/models/tree/master/research/audioset/vggish), using (transfer learning) finetuning. I initially started ...
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31 views

Why gpt-2 could apply to other tasks without fine-tune?

Language Models are Unsupervised Multitask Learners https://github.com/openai/gpt-2
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20 views

Problem regarding designing the generator function

I am implementing the paper Perceptual GAN for small object detection. The design is described by the picture given below. I have used Transfer Learning concept and used a pretrained model inside the ...
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0answers
12 views

Pretrained model entirely losing its properties

I am a newbie in the field of deep learning, so advance apologies if any mistake is there. I was trying to use pretrained models like BERT and GPT2 for generating language in our native language (say, ...
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12 views

How to get model predictions on all classes after applying Transfer Learning?

I have been following transfer learning with TFHub to implement transfer learning in my model for text classification. However, I do not understand how to get probabilities for all the classes (1000 ...
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0answers
10 views

Confusion regarding prediction results of SVM and ANN on feature vectors

I am making a custom image classifier using Transfer Learning on Inception V3. I have 3 classes of images with ~6K images each. The input dimension of the network is 500X500 and the output of the ...
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2answers
26 views

Does partial transfer learning require a lot of computer power?

I want to be sure my understanding of the problem is correct. I want to do image classification and current state of the art in my field is achieved by transfer learning with VGG16. Since image on ...
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1answer
391 views

How to add a CNN layer on top of BERT?

I am just playing with bert (Bidirectional Encoder Representation from Transformer) Research Paper Suppose I want to add any other model or layers like Convolutional Neural Network layers (CNN), Non ...
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30 views

Text classifiaction for large datasets using Transfer learning

I am trying to do text classification on a very large set of documents using the pretrained GPT model. The problem is GPT takes max sequence length $\le$ 1024. I can't truncate the data as I need to ...
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623 views

Transfer learning on yolo using keras

I am working on a project that uses object detection. I have logo images that need to be detected in a video. I am doing this in keras. I followed this blog to convert the yolo weights to a keras ...
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76 views

TensorFlow: how to restore pre-trained meta model and pass it's weights and biases to the optimizer?

I trained a model on a specific dataset and saved it as a meta, I want to restore the model and use its weights and biases on another dataset the code isn't mine but I'm trying to restore the ...
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26 views

Transfer learning, saving final FC layer only

I've written some code for transfer learning classifier using pytorch/ResNet. I replaced the final FC layer with an FC layer with the correct number of output classes. I froze all layers except for ...
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2answers
159 views

Feeding 3 consecutive video frames to a CNN to track a tennis ball

I want to use CNN transfer learning to track a tennis ball from TV broadcasts of tennis matches. I used VGG annotating tool annotation tool link (use version 1 of the tool for compatibility with ...
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2answers
176 views

meaning of fine-tuning in nlp task

There are two types of transfer learning model. One is feature extraction, where the weights of the pre-trained model are not changed while training on the actual task and other is the weights of the ...
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1answer
40 views

Transfer learning for a regression problem

if my understanding is correct, in case of image classification and NLP, if I have a pre-trained model, to train on new data, I can reshape the data according to the pre-trained model. So there is no ...
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1answer
41 views

Selection of base model for transfer learning

Is there a golden rule which gives intuition on which base model needs to be used for a give image classification problem. Most of the articles gives the below details which says how to train the ...
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11 views

semi supervised learning using transfer learning and shared memory

I am reading a paper here and I am not sure I am understanding something. They claim to have 83% unsupervised on CIFAR 10, but they used something that is semi supervised. At the very least, they used ...
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231 views

How to arrange the dataset/images for CNN+LSTM

I am working on an image classification problem using Transfer Learning with Resnet50 as base model (in Keras) (For example Class A and Class B). There is a time factor involved in this ...
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1answer
78 views

Make the CNN to say “I don't know”

I am currently working on an image classification problem. To ease the implementation I used transfer learning in Keras with ...
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1answer
2k views

Default value of learning rate in adam optimizer - Keras

I am working on a image classification problem using Transfer Learning. Parameters used given below: Adam optimizer with learning rate - 0.0001 ...
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0answers
47 views

Finetuning pretrained inception_v3 in pytorch

I'm following this tutorial but I'm having some trouble with inception. Every architecture works successfully, but when I run the tutorial code for inception, I get the following error: ...
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98 views

Transfer Learning with CNN layer trainable True - Accuracy not improving

I am working on a image classification problem with 4 classes. And I am using Transfer Learning (Resnet50) to train the model. Below are the observation. Pre-trained weights are from ...
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852 views

Keras load pre-trained weights. Shape mismatch

I have some trouble loading pre-trained weights with Keras. Let's say I have a keras model model and that my weights are stored at ...
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1answer
172 views

How does BERT deal with catastrophic forgetting?

In the ULMFit paper authors propose a strategy of gradual unfreezing in order to deal with catastrophic forgetting. That is, when the model starts be fine-tuned according to a downstream task, there ...