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Applications de compression de réseau

R2025b
Compressez un réseau de neurones profond via la quantification, la compression des paramètres entraînables ou l’élagage

Générez du code pour des réseaux de Deep Learning en réduisant l’empreinte mémoire et les exigences de calcul.

Sélection d՚exemples

Generate INT8 Code for Deep Learning Network on Raspberry Pi

Generate INT8 Code for Deep Learning Network on Raspberry Pi

Generate code for deep learning network that performs inference computations in 8-bit integers.

Generate INT8 Code for Deep Learning Network on Cortex-M Target

Generate INT8 Code for Deep Learning Network on Cortex-M Target

Generate code for deep learning network that performs inference computations in 8-bit integers.

Prune Filters in a Detection Network Using Taylor Scores

Prune Filters in a Detection Network Using Taylor Scores

Reduce network size and increase inference speed by pruning convolutional filters in a you only look once (YOLO) v3 object detection network.

Code Generation for Sequence-to-Sequence Classification with Learnables Compression

Code Generation for Sequence-to-Sequence Classification with Learnables Compression

Generate code for LSTM network with learnables compression.

Compress Image Classification Network for Deployment to Resource-Constrained Embedded Devices

Compress Image Classification Network for Deployment to Resource-Constrained Embedded Devices

Compress the image classification network for deployment on a Raspberry Pi hardware.