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In the SqueezeNet paper, the authors demonstrated that a model compression technique called Deep Compression can be applied to SqueezeNet to further reduce the size of the parameter file from 5 MB to 500 KB. [1] Deep Compression has also been applied to other DNNs, such as AlexNet and VGG. [20]
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:
Because of the first-stage RLE compression (see above), the maximum length of plaintext that a single 900 kB bzip2 block can contain is around 46 MB (45,899,236 bytes). This can occur if the whole plaintext consists entirely of repeated values (the resulting .bz2 file in this case is 46 bytes long). An even smaller file of 40 bytes can be ...
Due to typical file system design, the amount of space allocated for a file is usually larger than the size of the file's data – resulting in a relatively small amount of unusable storage space for each file, called slack space or internal fragmentation.
This algorithm uses a dictionary compression scheme somewhat similar to the LZ77 algorithm published by Abraham Lempel and Jacob Ziv in 1977 and features a high compression ratio (generally higher than bzip2) [2] [3] and a variable compression-dictionary size (up to 4 GB), [4] while still maintaining decompression speed similar to other ...
Compression of an image to reduce file size (in Kb) is usually "lossy" and is not advised for featured pictures. Image compression will reduce download times and save disk space, but it does so at the expense of fine detail and overall image quality. If in doubt, when saving JPEG files, always select the "maximum" quality setting.