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miniresnet

Audio Classification
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@@ -65,8 +65,8 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
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  | Model | Format | Resolution | Series | Activation RAM (KiB) | Runtime RAM (KiB)| Weights Flash (KiB) | Code Flash (KiB) | Total RAM (KiB) | Total Flash (KiB)| STM32Cube.AI version |
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  |-------------------|--------|------------|---------|----------------|-------------|---------------|------------|-------------|-------------|-----------------------|
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- | [MiniResNet 1stack ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 59.89 | 5.38 | 123.6 | 56.9 | 65.27 | 180.5 | 10.0.0 |
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- | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 59.89 | 8.37 | 431.1 | 63.69 | 68.26 | 494.9 | 10.0.0 |
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  ### Reference inference time based on ESC-10 dataset
@@ -74,8 +74,8 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
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  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
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  |-------------------|--------|------------|------------------|------------------|-------------|-----------------|-----------------------|
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- | [MiniResNet 1stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 1 CPU | 160 MHz | 92.25 | 10.0.0 |
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- | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 1 CPU | 160 MHz | 142.69 | 10.0.0 |
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  ### Accuracy with ESC-10 dataset
@@ -86,10 +86,10 @@ The reason this metric is used instead of patch-level accuracy is because patch-
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  | Model | Format | Resolution | Clip-level Accuracy |
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  |-------|--------|------------|----------------|
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- | [MiniResNet 1stack ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl.h5) | float32 | 64x50x1 | 89.9% |
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- | [MiniResNet 1stack ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | 88.9% |
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- | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl.h5) | float32 | 64x50x1 | 92.4% |
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- | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | 93.6% |
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  ## Retraining and Integration in a simple example:
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  | Model | Format | Resolution | Series | Activation RAM (KiB) | Runtime RAM (KiB)| Weights Flash (KiB) | Code Flash (KiB) | Total RAM (KiB) | Total Flash (KiB)| STM32Cube.AI version |
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  |-------------------|--------|------------|---------|----------------|-------------|---------------|------------|-------------|-------------|-----------------------|
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+ | [MiniResNet 1stack ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 59.89 | 5.38 | 123.6 | 56.9 | 65.27 | 180.5 | 10.0.0 |
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+ | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 59.89 | 8.37 | 431.1 | 63.69 | 68.26 | 494.9 | 10.0.0 |
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  ### Reference inference time based on ESC-10 dataset
 
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  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
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  |-------------------|--------|------------|------------------|------------------|-------------|-----------------|-----------------------|
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+ | [MiniResNet 1stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 1 CPU | 160 MHz | 92.25 | 10.0.0 |
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+ | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | B-U585I-IOT02A | 1 CPU | 160 MHz | 142.69 | 10.0.0 |
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  ### Accuracy with ESC-10 dataset
 
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  | Model | Format | Resolution | Clip-level Accuracy |
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  |-------|--------|------------|----------------|
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+ | [MiniResNet 1stack ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl.h5) | float32 | 64x50x1 | 89.9% |
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+ | [MiniResNet 1stack ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_1stacks_64x50_tl/miniresnet_1stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | 88.9% |
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+ | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl.h5) | float32 | 64x50x1 | 92.4% |
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+ | [MiniResNet 2stacks ](https://github.com/STMicroelectronics/stm32ai-modelzoo/audio_event_detection/miniresnet/ST_pretrainedmodel_public_dataset/esc10/miniresnet_2stacks_64x50_tl/miniresnet_2stacks_64x50_tl_int8.tflite) | int8 | 64x50x1 | 93.6% |
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  ## Retraining and Integration in a simple example:
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