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  RAYnet-1A is a convolutional neural network (CNN) architecture designed for image classification. With 23 million parameters, it is optimized to find the best balance between accuracy and computational efficiency. Its intelligent design makes it particularly suitable for applications that require fast performance, such as real-time processing on mobile or embedded devices.
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  License Information
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  This model is distributed under the Apache 2.0 License. You can find a full copy of the license in the LICENSE file of the repository.
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  RAYnet-1A is a convolutional neural network (CNN) architecture designed for image classification. With 23 million parameters, it is optimized to find the best balance between accuracy and computational efficiency. Its intelligent design makes it particularly suitable for applications that require fast performance, such as real-time processing on mobile or embedded devices.
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+ We encourage you to test image detection and image segmentation.
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  License Information
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  This model is distributed under the Apache 2.0 License. You can find a full copy of the license in the LICENSE file of the repository.
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