Results 11 to 20 of about 3,225,031 (302)
Long-term recurrent convolutional networks for visual recognition and description [PDF]
Computer Vision and Pattern Recognition, 2014 Models based on deep convolutional networks have dominated recent image interpretation tasks; we investigate whether models which are also recurrent, or “temporally deep”, are effective for tasks involving sequences, visual and otherwise.
Jeff Donahue +6 more
semanticscholar +1 more source
Dostarlimab for Primary Advanced or Recurrent Endometrial Cancer.
New England Journal of Medicine, 2023 BACKGROUND Dostarlimab is an immune-checkpoint inhibitor that targets the programmed cell death 1 receptor. The combination of chemotherapy and immunotherapy may have synergistic effects in the treatment of endometrial cancer.
M. Mirza +30 more
semanticscholar +1 more source
Speech recognition with deep recurrent neural networks [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2013 Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training methods such as Connectionist Temporal Classification make it possible to train RNNs for sequence labelling problems where the input-output alignment is ...
Alex Graves +2 more
semanticscholar +1 more source
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 The predictive learning of spatiotemporal sequences aims to generate future images by learning from the historical context, where the visual dynamics are believed to have modular structures that can be learned with compositional subsystems.
Yunbo Wang +6 more
semanticscholar +1 more source
Recurrent Neural Networks for Multivariate Time Series with Missing Values [PDF]
Scientific Reports, 2016 Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values.
Zhengping Che +4 more
semanticscholar +1 more source
A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
Neural Computation, 2019 Recurrent neural networks (RNNs) have been widely adopted in research areas concerned with sequential data, such as text, audio, and video. However, RNNs consisting of sigma cells or tanh cells are unable to learn the relevant information of input data ...
Yong Yu +3 more
semanticscholar +1 more source
Conditional Random Fields as Recurrent Neural Networks [PDF]
IEEE International Conference on Computer Vision, 2015 Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have attempted to harness the capabilities of deep learning techniques for image recognition to tackle pixel-level labelling tasks ...
Shuai Zheng +7 more
semanticscholar +1 more source
Survival with Cemiplimab in Recurrent Cervical Cancer.
New England Journal of Medicine, 2022 BACKGROUND Patients with recurrent cervical cancer have a poor prognosis. Cemiplimab, the fully human programmed cell death 1 (PD-1)-blocking antibody approved to treat lung and skin cancers, has been shown to have preliminary clinical activity in this ...
K. Tewari +34 more
semanticscholar +1 more source
Scale-Recurrent Network for Deep Image Deblurring [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 In single image deblurring, the "coarse-to-fine" scheme, i.e. gradually restoring the sharp image on different resolutions in a pyramid, is very successful in both traditional optimization-based methods and recent neural-network-based approaches. In this
Xin Tao +5 more
semanticscholar +1 more source
Pembrolizumab for Persistent, Recurrent, or Metastatic Cervical Cancer.
New England Journal of Medicine, 2021 BACKGROUND Pembrolizumab has efficacy in programmed death ligand 1 (PD-L1)-positive metastatic or unresectable cervical cancer that has progressed during chemotherapy.
N. Colombo +18 more
semanticscholar +1 more source