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Tags
- EECS 498-007/598-005
- computer vision
- cv
- FORTRAN
- Graph Neural Networks
- cs224w
- GNN
- format이 없는 입출력문
- object detection
- image classification
- 산술연산
- 내장함수
- human keypoints
- feature cropping
- tensor core
- print*
- implicit rules
- gfortran
- fortran90
- implicit rule
- L2 distance
- L1 distance
- data-driven approach
- cross-entropy loss
- multiclass SVM loss
- parametric approach
- geometric viewpoint
- visual viewpoint
- algebraic viewpoint
- Semantic Gap
- computational graph
- roi align
- Fully convolutional network
- Image captioning
- Transposed Convolution
- Panoptic segmentation
- Upsampling
- Hyperparameter
- loss function
- autograd
- ROI pooling
- faster r-cnn
- fast r-cnn
- R-CNN
- Instance Segmentation
- Semantic Segmentation
- pytorch
- linear classifier
- Regularization
- Nearest Neighbor
- TENSOR
- numpy
- KNN
- sqrt
- hardware
- GPU
- Module
- Mod
- Parameter
- Software
- CPU