Title: P3: preparing for interview and reading paper [2024-02-28 Wed]
detection networks. It uses predefined anchor boxes and their
pyramides. There is a sliding window, a box-regression layer
(reg) and a box-classification layer (cls).

Anchor-free object detection methods is CenterNet, FCOS
(Fully Convolutional One-Stage Object Detection) and
DETR (DEtection TRansformers)
😶 #dailyreport #cv #objectdetection #fsl #deeplearning

Title: P2: preparing for interview and reading paper [2024-02-28 Wed]
- Learn-to-Parameterize - param eterizing the base learner or
some subparts of base learner for a novel task so that it can
address this task specifically. meta learner generate weights
for base learner.
- Learn-to-Adjust
- Learn-to-Remember

Also this article have good overview of all ML tasks.

Region Proposal Network (RPN) is a backbone of first object #dailyreport #cv #objectdetection #fsl #deeplearning

Title: P0: preparing for interview and reading paper [2024-02-28 Wed]
Few shot learning (FSL):
- 2023 A Survey on Machine Learning from Few Samples
CV Object detecttion:
- 2016 Faster R-CNN: Towards Real-Time Object
Detection with Region Proposal Networks
- 2018 Mask R-CNN
- 2015 YOLO

Most solutions for FSL in non-deep period before 2015
was generative based, but then discriminative.
Discriminative approaches is: #dailyreport #cv #objectdetection #fsl #deeplearning

Title: P3: preparing for interview and reading paper [2024-02-28 Wed]
detection networks. It uses predefined anchor boxes and their
pyramides. There is a sliding window, a box-regression layer
(reg) and a box-classification layer (cls).

Anchor-free object detection methods is CenterNet, FCOS
(Fully Convolutional One-Stage Object Detection) and
DETR (DEtection TRansformers)
😶 #dailyreport #cv #objectdetection #fsl #deeplearning

Title: P2: preparing for interview and reading paper [2024-02-28 Wed]
- Learn-to-Parameterize - param eterizing the base learner or
some subparts of base learner for a novel task so that it can
address this task specifically. meta learner generate weights
for base learner.
- Learn-to-Adjust
- Learn-to-Remember

Also this article have good overview of all ML tasks.

Region Proposal Network (RPN) is a backbone of first object #dailyreport #cv #objectdetection #fsl #deeplearning

Title: P0: preparing for interview and reading paper [2024-02-28 Wed]
Few shot learning (FSL):
- 2023 A Survey on Machine Learning from Few Samples
CV Object detecttion:
- 2016 Faster R-CNN: Towards Real-Time Object
Detection with Region Proposal Networks
- 2018 Mask R-CNN
- 2015 YOLO

Most solutions for FSL in non-deep period before 2015
was generative based, but then discriminative.
Discriminative approaches is: #dailyreport #cv #objectdetection #fsl #deeplearning

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fly51fly (@fly51fly)

INRIA Lille와 Google DeepMind 연구진이 표본 효율적인 몬테카를로 플래닝 기법인 "Sample-efficient Monte-Carlo planning" 논문을 arXiv에 공개했다. 강화학습·계획 분야에서 적은 샘플로 더 효율적으로 탐색하는 새로운 연구로 보인다.

https://x.com/fly51fly/status/2045252557430493624

#reinforcementlearning #planning #montecarlo #deeplearning #arxiv