Questions tagged [transfer-learning]

Transfer learning is the process of learning a set of characteristics from one data and applying this "knowledge" to another similar dataset (i.e. using the same model across datasets).

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Can CNNs detect features of different images?

In lecture, we talked about “parameter sharing” as a benefit of using convolutional networks. Which of the following statements about parameter sharing in ConvNets are true? (Check all that apply.) ...
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What's the definition of retraining?

In transfer learning, we always use new data to retrain the pre-trained model. But, what is the specific and official definition of retraining? Or what papers mentioned this definition, in transfer ...
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Error when trying Transfer Learning

I'm trying to train a model which is an extension of Google's Inception-V3 for the purpose of recognizing and classifying whether there is any pneumonia using x-ray images. I've used Tensorflow-Hub ...
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Transfer Learning Question: Extending the Functionality of a Multipose-Estimation Machine Learning Model?

I have experimented with a number of different machine learning models used for pose estimation. Most of them output a heatmap and offsets for the detected person(s) in the image. I really like the ...
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How to choose layer from which to unfreeze image classification model

I'm wondering what steps do you take to decide on the part of the model to unfreeze. Do you do multiple experiments? Since the use of GPU is expensive, you must have some guidelines. Note: I know ...
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How to help neuronal network with an other model

I am working on an image classification problem, the input data normally is images to classify, but I thought latitude and longitude would play something on these satellite images. I sorted by ...
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Keras bug NasNetlarge no top

I am trying to use NasNetlarge in Keras without the top but I cant get rid of the top: ...
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Transfer learning + Selective Fine Tuning

This is a two part question: Background: I have a rather small set (thousands) of medical images. I am using pretrained models off of kersa.applications without ...
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Fine-tuning pre-trained Word2Vec model with Gensim 4.0

With Gensim < 4.0, we can retrain a word2vec model using the following code: ...
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TensorFlow - TFRecords load and transform images with bounding boxes

I'm trying to build a 'Car Classifier' using TensorFlow. I have 1000 labelled JPG images, 800x800, complete with bounding boxes and associated annotations.coco.json; split into train/validate/test ...
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Real-life applications/examples of transfer learning approaches

I recently read a nice, informative paper titled 'A Survey on Transfer Learning'. It mentions 3 settings of transfer learning - inductive, transductive, and unsupervised. At the same time, it states ...
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How to load a saved model in TensorFlow?

This is my code in Python: ...
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Why is convnet transfer learning taking so long?

I am using transfer learning to train a binary image classification model using keras' pretrained VGG16 model. The code can be found below : ...
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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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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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GTX 1080t ti rans out of memory

I have 60000 images divided into two classes. I have tried to build transfer learning with pretrained ResNet50 but my new GTX 1080 ti returns -1 after couples of epochs. My guess is that it runs out ...
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Dealing with little available data: transfer learning

Suppose I seek to predict a certain numerical value, whereby the data set which contains the predetermined correct labels is only very small. However, I'm also provided a large data set with a label ...
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Does transfer learning make sense for small neural networks with only one or two hidden layers?

I am testing transfer learning on rather small neural networks with only two hidden layers of 20 neurons on tabular data. None of my experiments yields any improvement over a basic neural network. Is ...
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ImageNet vs CIFAR pre-trained models for biomedical image classification

I'm doing research on transfer learning for biomedical image classification, mainly skin lesion classification. From what I know, both CIFAR and ImageNet are pre-trained on natural images and not ...
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Why not using linear regression for finetuning the last layer of a neural network?

In transfer learning, often only the last layer of the network is retrained using gradient descent. However, the last layer of a common neural network performs only a linear transformation, so why do ...
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Pretrained model for spectrogram images

I'm working on a sound classification problem. For that, I'm converting the audio signals into spectrogram images and using transfer learning to classify them. Currently I'm using pretrained models ...
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Latent space for cross domain numerical features

I would like to find the shared latent space between two set of features. I have source and target domain features already extracted from images. I have 4 set of feature vectors for normal and ...
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1 answer
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What's the difference between transfer learning and feature extraction in CNN?

So from what i understand, transfer learning is the fact of training a model on a dataset where you have a lot of data, then keeping most of trained coefficients, and only re-training the last layer ...
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Transfer learning with many small datasets

Context I am working on a NLP-model that can classify documents into one of N categories. I have document data from a number of different customers. The document topics are similar across customers ...
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Transfer learning with Keras for medical image classification

Good afternoon; I'm trying to do Transfer Learning from pre-trained model on imagenet to solve a classification task with Lung CT slices. These slices are stored in ...
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From Patch-based Classifier to Full Image classifier

I was wondering if it is feasible to train patch-based image classifier, due to small amount of data, and then use it in order to initialize training for full image classification, but this time on ...
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Multi-Class CNN model predicting only one class but still the accuracy is high

Before marking the question as repeated, note that I have read most of them but did not find the solution. I have given all the information on model below so please give advice for it. I am working ...
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1 vote
1 answer
283 views

Negative examples for a Yes/No image classification neural network

I am trying to retrain a neural network using transfer learning that can classify whether an image has a certain object, say, a car. My positive sample dataset is quite small, only 2500~ images. It ...
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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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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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How to apply transfer learning on a time-to-failure 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 when ...
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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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336 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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342 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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Training InceptionV3/Resnet on custom data with CoreML/CreateML

I'm new to the CoreML/CreateML scene. I know that there is an image classifier built by Apple that can be easily trained by drag/dropping data, with pretty good accuracy. What I am wondering is, is ...
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1 vote
2 answers
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Simple question about prediction classes of item in question vs not item in question

Let's say I wanted to use transfer learning to train a model to detect object A vs everything else. In this case, do I provide 2 types of input, images of object A and images of everything else, and ...
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1 vote
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How to change the pooling to adaptpooling before FC layer in the Inception-ResnetV2 model in keras

Now I am using the keras model: Inception-ResnetV2 to do image classification using transfer learning. The main code about this model is as following: ...
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1 vote
1 answer
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Transfer learning: Poor performance with last layer replaced

I am using a transfer learning approach. For this I followed the tensorflow for poets tutorial. I use a pre-trained InceptionV3 architecture trained on the Imagenet dataset. The last layer and the ...
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1 answer
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Dealing with pre-trained model for grayscale images

I would like to do Transfer Learning using one of the novel networks such as VGG, ResNet, Inception, etc. The problem is that my images are grayscale (1 channel) since all the above mentioned models ...
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Transfer learning: As simple as running trained models on new data?

So there's a domain of interest where the machine learning models are all specific to one entity. Let's call it a building. So there's a model made for every building. The literature in the domain all ...
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How to get attention weights from BERT

I am trying to make transfer learning in the encoder and decoder parts of the transformer. The encoder is a whole feature extraction part and there is the feature extraction part in the decoder too(I ...
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Transfer Learning transformer architecture

I would like to make transfer learning for transformer architecture. The input of the encoder and decoder must be word embeddings. So I wanted to use a pre-trained BERT model as a word embedder and ...
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Transfer learning on the same samples for progressively more specific classification

I have a classification task in which classes exist within a directed graph. That is a class may have subclasses which share an is-a relationship with their parent class. Now, I have a relatively ...
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Model transfer with limit to none label information

I have this problem I hope to get some help here. Say I have a type of product A whose measurements are X_A and an outcome property is ...
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Train model using Transfer Learning, the validation accuracy not learning

I am new to transfer learning. I am doing face mask detection in 4 classes(no facemask wearing, incorrect facemask wearing, correct facemask wearing, double mask wearing). My objective is to compare ...
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183 views

model.fit vs model.evaluate gives different results?

The following is a small snippet of the code, but I'm trying to understand the results of model.fit with train and test dataset vs the model.evaluate results. I'm not sure if they do not match up or ...
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Finetune XLM-RoBERTa on Tensorflow

I want to finetune pre-trained XLM-RoBERTa from HuggingFace for Text classification. I have categorical data in English. I want to finetune model on Tensorflow-keras. Can anyone let me know how can I ...
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174 views

Finetune XLM-RoBERTa on TF-keras for text classification

I am trying to finetune pre-trained XLM-RoBERTa on Tensorflow-keras. I am using dataset in English for text classification. I have used xlm-roberta-base tokenizer to tokenize the sentences. I am using ...
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Baseline model and transfer learning

I've tried to find any guidance on using transfer learning when building baseline models for ML projects (CNN in my case) but found no clues on good practices in the matter. My logic says that no ...
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How to stack Transfer Learning models in a Sequential

To make a nice architecture, I wanted to stack Transfer Learning models one over the other. The three models I wanted to stack were : VGG16 InceptionV3 Resnet50 So, I defined the three models as ...
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