Preparing a short paper for ICML

[amitkumarj441]

ICML 2019 Conference: https://icml.cc/Conferences/2019/CallForPapers

Sample paper format: https://media.neurips.cc/Conferences/ICML2019/Styles/example_paper.pdf

Google Blog: https://ai.googleblog.com/2018/09/introducing-inclusive-images-competition.html

Relevant Papers:

1. https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf

ILSVRC2017 Challenge Winners:
ILSVRC 2017: http://image-net.org/challenges/LSVRC/2017/results

[1] Wang F, Jiang M, Qian C, et al. Residual Attention Network for Image Classification[J]. arXiv preprint arXiv:1704.06904, 2017.

[2] He K, Zhang X, Ren S, et al. Deep residual learning for image recognition[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 770-778.

[3] Szegedy C, Ioffe S, Vanhoucke V, et al. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning[C]//AAAI. 2017: 4278-4284.

[4] Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation[J]. arXiv preprint arXiv:1505.04597, 2015.

[5] Lin T Y, Dollár P, Girshick R, et al. Feature pyramid networks for object detection[J]. arXiv preprint arXiv:1612.03144, 2016.

[6] Shrivastava A, Sukthankar R, Malik J, et al. Beyond skip connections: Top-down modulation for object detection[J]. arXiv preprint arXiv:1612.06851, 2016.

[7] Zeng X, Ouyang W, Yan J, et al. Crafting GBD-Net for Object Detection[J]. arXiv preprint arXiv:1610.02579, 2016.

[dowhilefalse]

Great.
And what would be the contribution of our paper. I am thinking about what themes do we put in.

[amitkumarj441]

@dowhilefalse So here is an abstract format of the paper:

• Abstract
• Introduction
• Inclusive Net Module Architecture (or the module name like ResNet based or DenseNet etc.); on which we conducted the final experiments
  • Predictive model
• Evaluation Experiment
  • ** (need to give an overview of how the above model actually fits for training)
  • Dataset
  • Training and Prediction
  • Evaluation Measure
  • Result
• Conclusion

References: Look at these references

1. https://nips2018vigil.github.io/static/papers/accepted/36.pdf
2. https://nips2018vigil.github.io/static/papers/accepted/29.pdf

[dowhilefalse]

Sorry for the delay.
That's clear framework.
But more importantly, I guess we will first need to list our ideas which is innovative approaches.
What do you think