DL_Froggy Jump_Quiz2

Froggy Jumps

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Siva Ranjini

India

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Froggy Jumps DL_Froggy Jump_Quiz2Versión en línea Choose the correct option por Siva Ranjini 1 ResNet won which competition in 2015? a ImageNet ILSVRC 2015 classification (and also the COCO 2015 detection challenge) b PASCAL VOC 2015 detection c The MICCAI BraTS 2015 challenge 2 When the input and output dimensions of a residual block differ (because of a channel change or spatial downsampling), the shortcut path uses: a A 1×1 convolution to project to the new dimensions b Zero-padding only and no learned parameters c The block is skipped entirely 3 The two main families of skip connection in modern deep learning are: a Additive and concatenative b Forward and backward c Linear and non-linear 4 In Faster R-CNN, the output of RoI Pooling is most directly fed into: a Two parallel heads — a softmax class classifier and a bounding-box regressor b A non-maximum suppression block c The Region Proposal Network 5 Which loss is most often added to categorical cross-entropy specifically to combat class imbalance in segmentation (foreground ≪ background)? a Focal loss or Dice loss b L2 / mean-squared error c Hinge loss 6 How many resolution levels does the original U-Net's contracting path have, including the bottleneck? a 5 b 6 c 3 7 The defining innovation of ResNet (He et al., 2015) is: a Adding identity skip connections, the block output is F(x) + x b Using only 1×1 convolutions throughout the network c Replacing ReLU with a smoother activation

Froggy Jumps

DL_Froggy Jump_Quiz2Versión en línea

Choose the correct option

por Siva Ranjini

ResNet won which competition in 2015?

ImageNet ILSVRC 2015 classification (and also the COCO 2015 detection challenge)

PASCAL VOC 2015 detection

The MICCAI BraTS 2015 challenge

When the input and output dimensions of a residual block differ (because of a channel change or spatial downsampling), the shortcut path uses:

A 1×1 convolution to project to the new dimensions

Zero-padding only and no learned parameters

The block is skipped entirely

The two main families of skip connection in modern deep learning are:

Additive and concatenative

Forward and backward

Linear and non-linear

In Faster R-CNN, the output of RoI Pooling is most directly fed into:

Two parallel heads — a softmax class classifier and a bounding-box regressor

A non-maximum suppression block

The Region Proposal Network

Which loss is most often added to categorical cross-entropy specifically to combat class imbalance in segmentation (foreground ≪ background)?

Focal loss or Dice loss

L2 / mean-squared error

Hinge loss

How many resolution levels does the original U-Net's contracting path have, including the bottleneck?

The defining innovation of ResNet (He et al., 2015) is:

Adding identity skip connections, the block output is F(x) + x

Using only 1×1 convolutions throughout the network

Replacing ReLU with a smoother activation

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DL_Froggy Jump_Quiz2

Froggy Jumps

Sobre esta actividad

Creada por

Descarga la versión para jugar en papel

Top juegos

Froggy Jumps

OPEN UP 6 UNIT 1 VOCABULARY

Froggy Jumps

Quiz de Culpa mía película

Froggy Jumps

Sabiduría animal

Froggy Jumps

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Froggy Jumps

Salva a la Ranita

Froggy Jumps

DL_Froggy Jump_Quiz2Versión en línea

por Siva Ranjini

ResNet won which competition in 2015?

When the input and output dimensions of a residual block differ (because of a channel change or spatial downsampling), the shortcut path uses:

The two main families of skip connection in modern deep learning are:

In Faster R-CNN, the output of RoI Pooling is most directly fed into:

Which loss is most often added to categorical cross-entropy specifically to combat class imbalance in segmentation (foreground ≪ background)?

How many resolution levels does the original U-Net's contracting path have, including the bottleneck?

The defining innovation of ResNet (He et al., 2015) is:

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