Abstract: 1D, 2D and multidimensional convolutions are basic tools in deep learning, notably in convolutional neural networks (CNNs) and in computer vision (template matching, correlation trackers).

Abstract: Our study proposes a new approach for building extraction by introducing the deformable-convolution fusion feature (DCFF) module, based on the dual-attention network (DANet) and deformable ...

# FOR ENCODING IT, LET'S KEEP TRACK OF THE LENGTH OF THE NUMBER AND PUT A DELIMITTER FOR WHEN WE WANT TO DECODE ...

# we are trying to convert a list of strings into a single encoded string # then be able to deconde that single string back to it's orginal list ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a forward-looking technological achievement: the hybrid quantum-classical three-dimensional ...

Communication-system designers have always had to deal with trade-offs among data reliability, efficient use of available spectrum, data throughput, and cost. Error-correction coding (ECC) is one of ...

test and verify the Reed-Solomon codec. Each of these steps is important, and missing one results in developing hardware that does not work the first time and must be re-created. For example, it is ...