Results 261 to 270 of about 16,769 (297)

Multiscale Circuit Architecture Associated With Memory Dysfunction in Temporal Lobe Epilepsy

Advanced Science, EarlyView.
A multiscale precision‐mapping framework reveals that memory impairment in temporal lobe epilepsy arises from the convergence of focal medial temporal pathology, strategic white matter disconnection, and limbic‐centered metabolic network dysfunction.
Jiajie Mo, Qiwen Yuan, Pengfei Zhang, Lin Sang, Zhong Zheng, Baotian Zhao, Xiu Wang, Chao Zhang, Wenhan Hu, Xiaoqiu Shao, Jianguo Zhang, Ruijin Yang, Kai Zhang   +12 more
wiley   +1 more source

Advances in Weakly Supervised Learning of Morphology

, 2015
openaire   +4 more sources

Weakly supervised label learning flows [PDF]

Neural Networks
Accepted as a full length research article by Neural ...
Wenzhuo Song, You Lu, Bert Huang
exaly   +5 more sources

Weakly supervised foreground learning for weakly supervised localization and detection

Pattern Recognition, 2023
Modern deep learning models require large amounts of accurately annotated data, which is often difficult to satisfy. Hence, weakly supervised tasks, including weakly supervised object localization~(WSOL) and detection~(WSOD), have recently received attention in the computer vision community.
Jianxin Wu, Chen-Lin Zhang, Yin Li
exaly   +3 more sources

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology [PDF]

Medical Image Analysis, 2022
Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of tiles and classification problems are often weakly-supervised ...
, Faisal Mahmood, Elizabeth Alwers
exaly   +3 more sources

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Towards Safe Weakly Supervised Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
In this paper, we study weakly supervised learning where a large amount of data supervision is not accessible. This includes i) incomplete supervision, where only a small subset of labels is given, such as semi-supervised learning and domain adaptation; ii) inexact supervision, where only coarse-grained labels are given, such as multi-instance learning
Yu-Feng Li, Zhi-Hua Zhou, Yu-Feng Li
exaly   +3 more sources

Weakly Supervised Learning-based Table Detection

SN Computer Science, 2020
CNN has given the state-of-the-art results in computer vision and natural language processing (NLP) domain problems. This has motivated researchers to use deep learning-based techniques for document layout analysis. Due to recent advances in communication and in information technology, methods of data storage, extraction and processing are rapidly ...
A. A. Gurav, Manisha J. Nene
openaire   +1 more source