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Deep Quantized Representation for Enhanced Reconstruction
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Deep Quantized Representation for Enhanced Reconstruction
In this paper, we propose a data driven Deep Quantized Latent Representation (DQLR) for high-quality data reconstruction in the Shoot Apical Meristem (SAM) of Arabidopsis thaliana. Our proposed framework utilizes multiple consecutive slices to learn a low dimensional latent space, quantize it and perform reconstruction using the quantized representation.
In this paper, we propose a data driven Deep Quantized Latent Representation (DQLR) for high-quality data reconstruction in the Shoot Apical Meristem (SAM) of Arabidopsis thaliana. Our proposed framework utilizes multiple consecutive slices to learn a low dimensional latent space, quantize it and perform reconstruction using the quantized representation.
