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Learning to Segment the Tail [article]

Xinting Hu, Yi Jiang, Kaihua Tang, Jingyuan Chen, Chunyan Miao, Hanwang Zhang
2020 arXiv   pre-print
We call our approach Learning to Segment the Tail (LST).  ...  head to the data-poor tail.  ...  We thank all the reviewers for their constructive comments. This work was supported by Alibaba-NTU JRI, and partly supported by Major Scientific Research Project of Zhejiang Lab (No. 2019DB0ZX01).  ... 
arXiv:2004.00900v2 fatcat:f4ucuwxnxfay3ct3igzctetady

Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer [article]

Suhyeon Lee, Junhyuk Hyun, Hongje Seong, Euntai Kim
2020 arXiv   pre-print
We address this problem by transferring the contents of tail classes from synthetic to real domain.  ...  In this paper, we tackle the unsupervised domain adaptation (UDA) for semantic segmentation, which aims to segment the unlabeled real data using labeled synthetic data.  ...  Zhu et al. (2017) proposed to transfer the domain of images, and domain-transferred images can be used to learn the segmentation model.  ... 
arXiv:2012.12545v1 fatcat:qxdokvfw65ekto4cydmindcn2m

Unsupervised Discovery of the Long-Tail in Instance Segmentation Using Hierarchical Self-Supervision [article]

Zhenzhen Weng, Mehmet Giray Ogut, Shai Limonchik, Serena Yeung
2021 arXiv   pre-print
The goal of this paper is to propose a method that can perform unsupervised discovery of long-tail categories in instance segmentation, through learning instance embeddings of masked regions.  ...  Trained on COCO dataset without additional annotations of the long-tail objects, our model is able to discover novel and more fine-grained objects than the common categories in COCO.  ...  Acknowledgements This material is based upon work supported by the National Science Foundation under Grant No. 2026498, as well as a seed grant from the Institute for Human-Centered Artificial Intelligence  ... 
arXiv:2104.01257v1 fatcat:fju7jtlb6rhrnftb42qdxp52ri

The Devil is in Classification: A Simple Framework for Long-tail Object Detection and Instance Segmentation [article]

Tao Wang, Yu Li, Bingyi Kang, Junnan Li, Junhao Liew, Sheng Tang, Steven Hoi, Jiashi Feng
2020 arXiv   pre-print
They tend to suffer performance drop on realistic datasets that are usually long-tailed. This work aims to study and address such open challenges.  ...  Specifically, we systematically investigate performance drop of the state-of-the-art two-stage instance segmentation model Mask R-CNN on the recent long-tail LVIS dataset, and unveil that a major cause  ...  This suggests the box and mask head learning are less sensitive to long-tail training data than classification.  ... 
arXiv:2007.11978v5 fatcat:gigp7bmq3rcfjport7b67xtc4y

Unsupervised Object Detection with LiDAR Clues [article]

Hao Tian, Yuntao Chen, Jifeng Dai, Zhaoxiang Zhang, Xizhou Zhu
2021 arXiv   pre-print
The labeling process is carefully designed so as to mitigate the issue of long-tailed and open-ended distribution.  ...  Then, an iterative segment labeling process is conducted to assign segment labels and to train a segment labeling network, which is based on features from both 2D images and 3D point clouds.  ...  Acknowledgments The work is supported by the National Key R&D Program of China (2020AAA0105200), Beijing Academy of Artificial Intelligence.  ... 
arXiv:2011.12953v3 fatcat:oqwvshdmongjpjqs3uwl5ig73i

A Survey on Long-Tailed Visual Recognition

Lu Yang, He Jiang, Qing Song, Jun Guo
2022 International Journal of Computer Vision  
Finally, we provide several future directions for the development of long-tailed learning to provide more ideas for readers.  ...  In order to learn adequately for all classes, many researchers have studied and preliminarily addressed the long-tailed problem.  ...  Acknowledgements This work was supported by the National Key Research and Development Program of China (Grant No. 2021YFF0500900).  ... 
doi:10.1007/s11263-022-01622-8 fatcat:gtlfuw6igbd6xixqhynnqxubw4

Page 20 of The Journal of Biological Psychology Vol. 5, Issue 2 [page]

1963 The Journal of Biological Psychology  
The failure to confirm the results of McConnell and other experimenters (which state that head and tail segments regenerated in water show about the same savings of the initially acquired learning) may  ...  The planarians which regenerated from tail segments did not exhibit this ability.  ... 

Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training [article]

Sangjoon Park, Gwanghyun Kim, Jeongsol Kim, Boah Kim, Jong Chul Ye
2021 arXiv   pre-print
However, it is not clear how to find the optimal split without sacrificing the overall network performance.  ...  To amalgamate these methods and thereby maximize their distinct strengths, here we show that the Vision Transformer, a recently developed deep learning architecture with straightforward decomposable configuration  ...  By minimizing the loss with respect to the tail weight, the gradients of the local tails are passed reversely to the server.  ... 
arXiv:2111.01338v2 fatcat:ixwyhfpfvfh5dgkwcpanvuzlma

Deep Long-Tailed Learning: A Survey [article]

Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, Jiashi Feng
2021 arXiv   pre-print
Considering the rapid evolution of this field, this paper aims to provide a comprehensive survey on recent advances in deep long-tailed learning.  ...  Deep long-tailed learning, one of the most challenging problems in visual recognition, aims to train well-performing deep models from a large number of images that follow a long-tailed class distribution  ...  Afterward, learning to segment the tail (LST) [77] also divides the training samples into several balanced subsets, and handles each one based on class-incremental learning.  ... 
arXiv:2110.04596v1 fatcat:lpvt2x6cv5crxm2qxdctjrlkqq

Unlocking the Full Potential of Small Data with Diverse Supervision [article]

Ziqi Pang, Zhiyuan Hu, Pavel Tokmakov, Yu-Xiong Wang, Martial Hebert
2020 arXiv   pre-print
Following the standard few-shot learning protocol, we use the head classes for representation learning and the tail classes for evaluation.  ...  In particular, we use the richly annotated scene parsing dataset ADE20K to construct our realistic Long-tail Recognition with Diverse Supervision (LRDS) benchmark by splitting the object categories into  ...  novel forms of multi-task learning that are able to better combine the benefits of diverse labels is an important direction for future work.  ... 
arXiv:1911.12911v2 fatcat:tayre5ygxffoxjirv4vmymf3k4

The relative effectiveness of observing response vs predifferentiation pretraining on children's discrimination learning

Billie J. Vance, Alexander W. Siegel
1971 Psychonomic Science  
stimuli; (2) making a specific observing response to the critical feature of the stimuli; (3) simple familiarization with the stimui; and (4) developing a set to compare stimuli.  ...  This study was designed to assess the relative effectiveness of four components of pretraining on a subsequent simultaneous discriminaton and reversal: (1) making same-different judgments about the two  ...  All cat stimuli were exactly the same except for the type of tail. Tbe distinguishing feature of each stimulus (mouth or tail) fit entirely within the bottom segment of the console window.  ... 
doi:10.3758/bf03335559 fatcat:kw5regebojgajgrfg7ae3yesni

Deep learning method for comet segmentation and comet assay image analysis

Yiyu Hong, Hyo-Jeong Han, Hannah Lee, Donghwan Lee, Junsu Ko, Zhen-yu Hong, Ji-Young Lee, Ju-Hyung Seok, Hee Seon Lim, Woo-Chan Son, Insuk Sohn
2020 Scientific Reports  
First, each comet region must be located and segmented, and next, it is scored using common metrics (e.g., tail length and tail moment).  ...  Currently, most studies on comet assay image analysis have adopted hand-crafted features rather than the recent and effective deep learning (DL) methods.  ...  In contrast, DL can allow raw image data as input and learn to detect and segment comet in an end-to-end process.  ... 
doi:10.1038/s41598-020-75592-7 pmid:33144610 pmcid:PMC7609680 fatcat:pp3fvg22infclkspsruhg5iiei

Page 154 of The Biological Bulletin Vol. 82, Issue 1 [page]

1942 The Biological Bulletin  
Whether a head or a tail forms depends to a large extent upon the segment of the host into which the implant is inserted.  ...  An implant derived from the anterior end (segments 1-7) of a donor may give rise to a bud of either head or tail type (Sayles, 1940a).  ... 

Learning to rank audience for behavioral targeting in display ads

Jian Tang, Ning Liu, Jun Yan, Yelong Shen, Shaodan Guo, Bin Gao, Shuicheng Yan, Ming Zhang
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
Behavioral targeting (BT), which aims to sell advertisers those behaviorally related user segments to deliver their advertisements, is facing a bottleneck in serving the rapid growth of long tail advertisers  ...  segments.  ...  Each segment is labeled with keywords to indicate the interests of the users in the segment. For example, a segment labeled with "car buyer" indicates the users in this segment may want to buy cars.  ... 
doi:10.1145/2063576.2063666 dblp:conf/cikm/TangLYSGGYZ11 fatcat:jidbcm6cyvg7bojqastar3vmla

PartImageNet: A Large, High-Quality Dataset of Parts [article]

Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jie-Neng Chen, Shuai Liu, Cheng Yang, Qihang Yu, Alan Yuille
2022 arXiv   pre-print
It can be utilized for many vision tasks including Object Segmentation, Semantic Part Segmentation, Few-shot Learning and Part Discovery.  ...  This has the potential to improve the performance of algorithms for object recognition and segmentation but can also help for downstream tasks like activity recognition.  ...  These approaches mainly share a common learning strategy: 1) unsupervised learning, 2) explicit clustering to obtain the parts, 3) modeling the spatial relation between parts.  ... 
arXiv:2112.00933v2 fatcat:iysdgtt4vjdg3lmttw2ps45lgu
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