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Questions - deep-learning

Predict new coordinates given old coordinates in Tensorflow's Keras

The goal is to be able to predict a new set of (x1, y1), (x2, y2) coordinates when given the old set of (x1, y1), (x2, y2) coordinates. That is to say, if my old coordinates are (0, 0), (4, 4), I want...
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Grant Allan

python

deep-learning

neural-network

tf.keras

Votes: 0

Answers: 1

Latest Answer

You just need to use sequential models. As I understand you have inputs with size 4, and outputs with size 4 as well. In this case you would do something like: import tensorflow as tf from tensorflow ...
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Hakan Akgün

InvalidArgumentError: logits and labels must have the same first dimension, got logits shape [15488,3] and labels shape [32]

My code is not working I am getting InvalidArgumentError: logits and labels must have the same first dimension, got logits shape [15488,3] and labels shape [32] [[node sparse_categorical_crossentropy...
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M.Hamza

python

tensorflow

machine-learning

keras

deep-learning

Votes: 0

Answers: 1

Latest Answer

After your code layers.MaxPooling2D() you need to flatten the data before you apply it to the dense layer so add layers.Flatten()
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Gerry P

Multi Task Learning with different sample size in each pair input/output

I am implementing a MTL solution for a regression model in an already known benchmarking dataset for this kind of applications (School Dataset from Manash). I could efficiently train the model using 3...
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javier.desario

python

numpy

tensorflow

keras

deep-learning

Votes: 0

Answers: 0

openvino human pose estimation 0007

I am working with openvinotoolkit and I am trying to inference the model human-pose-estimation-0007 and that works fine on neural stick 2. Now I am looking for the original human-pose-estimation-0007 ...
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ssgakhal

deep-learning

openvino

pose-estimation

efficientnet

movidius

Votes: 0

Answers: 1

Latest Answer

Here is the repository for human pose estimation in PyTorch. https://github.com/Daniil-Osokin/lightweight-human-pose-estimation.pytorch
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Rommel_Intel

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