deep neural networks
Projects with this topic
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This is a segmentation model trained on seated Buddha Statue dataset collected from Google Images. The model can be used to segment seated Buddha Statue objects from images. The model is based on YOLO v8
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This projects implements neural-network controllers for two agent-based models: (i) a predator-prey model and (ii) a metabolic network model.
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a EMOTION RECOGNITION PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a FACE RECOGNITION PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY)
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a VOICE PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a HEARING PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a TRAFFIC COUNTING (TC) PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT MASKING PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT DETECTION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an OBJECT DETECTION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION (D) proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION (C) proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION (A1) PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a BRAIN PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an ASTRAL VISION PROXIA (C) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an ASTRAL VISION PROXIA when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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A simple NN that can increase the accuracy of existing object detectors.
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A Differentiable Raytracing Renderer allows using it as a layer in a Deep Neural Network.
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