태그
Transformer,
self attention,
DNN,
VIT,
attention,
MIT,
Vision,
accelerators,
ai semiconductor,
a^3,
han lab,
dataengine,
distributed training,
softmax attention,
linear attention,
efficient vit,
shift window,
window attention,
swin transformerr,
visioni transformer,
feed forward,
weight sharing,
conv loayer,
layer connection,
sparsely connected,
Segment Anything,
Vision Transformer,
Attention mechanism,
Vivado,
Inference,
Fully connected,
Back Propagation,
approximation,
ResNet,
Gradient Descent,
deep learning,
Neural Networks,
masking,
Vitis,
JTAG,
softmax,
LAYER,
ASIC,
training,
PL,
Fc,
FPGA,
DL,
Sam,
meta,
codesign,
hardware,
segment,
ps,
