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Quantization

97 papers with code · Methodology

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Detection of Structural Change in Geographic Regions of Interest by Self Organized Mapping: Las Vegas City and Lake Mead across the Years

29 Mar 2018JustGlowing/minisom

Time-series of satellite images may reveal important data about changes in environmental conditions and natural or urban landscape structures that are of potential interest to citizens, historians, or policymakers.

QUANTIZATION TIME SERIES

Rethinking floating point for deep learning

1 Nov 2018facebookresearch/deepfloat

In 16 bits, our log float multiply-add is 0. 59x the power and 0. 68x the area of IEEE 754 float16 fused multiply-add, maintaining the same signficand precision and dynamic range, proving useful for training ASICs as well.

QUANTIZATION

Integral Human Pose Regression

ECCV 2018 JimmySuen/integral-human-pose

State-of-the-art human pose estimation methods are based on heat map representation.

3D POSE ESTIMATION QUANTIZATION

Deep Triplet Quantization

1 Feb 2019thulab/DeepHash

We propose Deep Triplet Quantization (DTQ), a novel approach to learning deep quantization models from the similarity triplets.

IMAGE RETRIEVAL QUANTIZATION

Spreading vectors for similarity search

ICLR 2019 facebookresearch/spreadingvectors

Discretizing multi-dimensional data distributions is a fundamental step of modern indexing methods.

QUANTIZATION

Scalable Methods for 8-bit Training of Neural Networks

NeurIPS 2018 eladhoffer/convNet.pytorch

Armed with this knowledge, we quantize the model parameters, activations and layer gradients to 8-bit, leaving at a higher precision only the final step in the computation of the weight gradients.

QUANTIZATION

Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights

10 Feb 2017Zhouaojun/Incremental-Network-Quantization

The weights in the other group are responsible to compensate for the accuracy loss from the quantization, thus they are the ones to be re-trained.

QUANTIZATION

Soft Weight-Sharing for Neural Network Compression

13 Feb 2017KarenUllrich/Tutorial_BayesianCompressionForDL

The success of deep learning in numerous application domains created the de- sire to run and train them on mobile devices.

NEURAL NETWORK COMPRESSION QUANTIZATION

Learning compact binary descriptors with unsupervised deep neural networks

CVPR2016 2016 kevinlin311tw/cvpr16-deepbit

In this paper, we propose a new unsupervised deep learning approach called DeepBit to learn compact binary descriptor for efficient visual object matching.

IMAGE RETRIEVAL OBJECT RECOGNITION QUANTIZATION