neptune-ai/open-solution-salt-identification
Open solution to the TGS Salt Identification Challenge
PythonMIT
Issues
- 0
implement center_encoder l2 loss
#49 opened by jakubczakon - 0
experiment with dropout2d in the bottom layer
#76 opened by jakubczakon - 0
Implement PSPNet
#87 opened by jakubczakon - 3
- 5
- 1
OSError: [Errno 101] Network is unreachable
#93 opened by OsloAI - 0
Prepare data based on jigsaw puzzle
#90 opened by jakubczakon - 0
implement OCNet
#86 opened by jakubczakon - 0
experiment with loss schedules
#85 opened by jakubczakon - 0
- 0
Experiment with mean teacher
#71 opened by jakubczakon - 0
- 0
Implement SWA optimization
#48 opened by jakubczakon - 0
Implement post-processing block JOSE
#46 opened by jakubczakon - 1
Lovasz loss
#94 opened by yuanqing811 - 1
index 0 is out of bounds for axis 0 with size 0
#92 opened by OsloAI - 1
IndexError: too many indices for array
#91 opened by OsloAI - 0
explore other pretrained
#62 opened by jakubczakon - 0
add scse blocks after encoders
#88 opened by jakubczakon - 0
implement replication y + reflection x
#64 opened by jakubczakon - 0
try attention + squeeze and excite
#70 opened by jakubczakon - 0
experiment with large kernel matters
#83 opened by jakubczakon - 0
explore wavelet representation
#84 opened by jakubczakon - 0
Implement constrained size loss
#68 opened by jakubczakon - 0
Explore gabor filters representation
#43 opened by jakubczakon - 0
Implement Large Kernels Matter
#69 opened by jakubczakon - 1
Memory Allocation of Solution 4
#82 opened by xhh232018 - 0
Experiment with larger size
#75 opened by jakubczakon - 2
No module named 'neptune'
#66 opened by qinhui99 - 0
- 0
- 0
- 0
train with encoder LR smaller
#53 opened by jakubczakon - 0
CV for the best threshold
#57 opened by jakubczakon - 0
try mixed penaulty loss
#56 opened by jakubczakon - 0
explore border penaulty loss
#58 opened by jakubczakon - 0
explore focal loss
#63 opened by jakubczakon - 0
Increase unet resolution
#51 opened by jakubczakon - 0
explore squeeze and excitation block
#60 opened by jakubczakon - 0
Implement simple model averaging
#61 opened by jakubczakon - 0
explore replication padding in convolutions
#59 opened by jakubczakon - 0
try hypercolumn approach
#54 opened by jakubczakon - 0
Implement attention into decoders
#47 opened by jakubczakon - 2
- 0
Implement easy fine-tuning handling
#45 opened by jakubczakon - 0
Implement the lovasz softmax loss
#42 opened by jakubczakon - 0
implement batch norm in the decoder part
#44 opened by jakubczakon - 0
train on 128 + 32x2 pad
#39 opened by jakubczakon - 0
train with sgd
#41 opened by jakubczakon - 0
Experiment with random gradient
#38 opened by jakubczakon