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Questions tagged [transfer-learning]

For questions related to transfer learning, a machine learning method that focuses on storing knowledge gained while solving one problem in order to apply this knowledge to a different but related problem.

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Reasoning behind $Zero$ validation accuracy in the following ResNet50 model for classification

I have written this code to classify Cats and dogs using Resnet50. Actually while studying I came to the conclusion that Transfer learning gives very good accuracy for deep learning models, but I ...
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learning object recognition of primitive shapes through transfer learning problem

Question on transfer learning object classification (MobileNet_v2 with 75% number of parameters) with my own synthetic data: I made my own dataset of three shapes: triangles, rectangles and spheres. ...
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How can I improve the performance of a model trained to detect vehicle poses?

I'm looking for some suggestions on how to improve our vehicle image recognition. We have an online marketplace where customers submit photos of their vehicles. The photos need to meet certain ...
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Precise description of one-shot learning

I am working on classifying the Omniglot dataset and the different papers dealing with this topic describe the problem as one-shot learning (classification). I would like to nail down a precise ...
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1answer
72 views

What are the real-life applications of Transfer Learning in Machine Learning?

What are the real-life applications of Transfer Learning in Machine Learning? I am particularly interested in industrial applications of the concept.
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How to transfer learn Darknet YOLOv3

I've started getting into object detection in image. I have YOLOv3 neural network with Darknet framework. The network is pre-trained from COCO data set. Now I need to do some transfer learning in ...
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21 views

Training, validation loss and accuracy yolov3?

This is a version of Yolo V3 implemented in PyTorch – YOLOv3 in PyTorch I am trying to use transfer learning to train this yolov3 implementation following the directions given in this post. This is ...
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1answer
32 views

Transfer learning to train only for a new class while not affecting the predictions of the other class

I am basically interested in vehicle on the road. YoloV3 pytorch is giving a decent result. So my interested Vehicles Car ...
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1answer
110 views

How is transfer learning used to mitigate catastrophic forgetting in neural networks?

How can transfer learning be used to mitigate catastrophic forgetting. Could someone elaborate on this?
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1answer
56 views

What are the most common methods to enable neural networks to adapt to changing environments?

For real applications, concept drifts often exist, i.e., the relationship between the input and output changes overtime. Thus, we need our AI or machine learning system to quickly adapt to the ...
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2answers
143 views

What is the difference between learning without forgetting and transfer learning?

I would like to incrementally train my model with my current dataset and I asked this question on Github issues, which is what I'm using SSD MobileNet v1: https://github.com/tensorflow/models/issues/...
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29 views

Is convergence to a local minima more likely with transfer learning?

While doing transfer learning where my two problems are face-generation and car-generation is it likely that, if I use the weights of one problem as the initialization of the weights for the other ...
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46 views

Paper & code for “unsupervised domain adaptation” for regression task

Does anyone know a paper or code that does "unsupervised domain adaptation" for regression task? I saw most of the papers were benchmarked on classification tasks, not regression. I want to do ...
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Binary annotations on large, heterogenous images

I'm working on a deep learning project and have encountered a problem. The images that I'm using are very large and extremely detailed. They also contain a huge amount of necessary visual information, ...
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1answer
46 views

Are there any better visual models for transfer rather than ImageNet?

Similar to the recent pushes in Pretrained Language Models (BERT, GPT2, XLNet) I was wondering if such a thrust exists in Computer Vision? From my understanding, it seems the community has converged ...
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23 views

Training a reinforcement learning model with multiple images

I am tentatively trying to train a deep reinforcement learning model the maze escaping task, and each time it takes one image as the input (e.g., a different "maze"). Suppose I have about $10K$ ...
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8k views

Is it possible to train a neural network incrementally?

I would like to train a neural network where the output classes are not (all) defined from the start. More and more classes will be introduced later based on incoming data. This means that, every time ...
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1answer
484 views

Why does unsupervised pre-training help in deep learning?

What is the effectiveness of pre-training of unsupervised deep learning? Does unsupervised deep learning actually work?