用YOLOv3 模型在一个开源的人手检测数据集oxford hand上做人手检测,并在此基础上做模型剪枝。对于该数据集,对 YOLOv3 进行 channel pruning 之后,模型的参数量、模型大小减少 80% ,FLOPs 降低 70%,前向推断的速度可以达到原来的 200%,同时可以保持 mAP 基本不变(可以参照后面的表格,后面有时间的话会在其他数据...
Therefore, compression technologies with lossless or near-lossless model precision, such as pruning, quantization, and knowledge distillation, are used to implement automatic model compression and optimization, and automatic iteration of model compression and retraining to control the loss of model precision...
classModelPruningFinished(View source) Properties class-string[]$models The class names of the models that were pruned. Methods void __construct(class-string[] $models) Create a new event instance. Details at line 20 void__construct(class-string[] $models) ...
Principle of cell-based NAS and model pruning Test benches and datasets Cell-based CNN construction for bearing fault classification Cell-based CNN for bearing RUL prediction Model pruning for proposed cell-based CNNs Conclusion Data availability References Acknowledgements Funding Author information Ethics...
If you train the model on a large amount of internal data, without first pruning the dataset for only the highest quality examples you could end up with a model that performs much worse than expected. Use the Create custom model wizard Azure AI Foundry portal provides the Create custom model...
Automatically tune quantization and pruning to meet accuracy goals. Distill knowledge from a larger model (“teacher”) to a smaller model (“student”) to improve the accuracy of the compressed model. Customize quantization with advanced techniques such as SmoothQuant, layer-wise quantization, and ...
If the number of packed multicast sources to be pruned exceeds the maximum number of multicast sources that can be packed in a single Join/Prune message (calculated based on the MTU of the interface), only some multicast sources are packed and sent to the RP for pruning. Traffic of the ...
Disaster recovery and redundancy:Backup models, data and configurations regularly in the event of disasters. With redundancy, you can handle system failures without impacting model availability. Ethical model development:Anticipate, discover and correct biases in training data and model outputs that can ...
TNN supports INT8 WINOGRAD algorithm, (input 6bit), further reduces the model calculation complexity without sacrificing the accuracy. TNN supports mixed-precision data in one model, speeding up the model's calculation speed while preserving its accuracy. Memory optimization Efficient "memory pool" im...
Each continuous motion segment of the robot (without stopping or turning) was represented as an ASR (consisting of multiple boundary elements from sonar data). The robot was able to use the final network of ASRs it has built using the split and merge algorithm to find its way back ‘home...