Results 71 to 80 of about 9,325,572 (289)
IEEE Access, 2019 Accurate segmentation of brain tumor is an indispensable component for cancer diagnosis and treatment. In this paper, we propose a novel brain tumor segmentation method based on multi-cascaded convolutional neural network (MCCNN) and fully connected ...
Kai Hu +7 more
doaj +1 more source
Chinese Sequence Labeling Based on Stack Pre-training Model
Journal of Harbin University of Science and Technology, 2022 Sequence labeling is an important task in natural language processing. In this paper, according to the relevance of tasks, we use stacking pretraining model to extract features, segment words, and name entity recognition/chunk tagging.Through in-depth ...
LIU Yu-peng, LI Guo-dong
doaj +1 more source
Bacteria‐Trained, MnO2‐Armored Dendritic Cells for Immunotherapy
Advanced Materials, EarlyView.MnO2‐armored, bacteria‐trained dendritic cells undergo tumor‐responsive mechanical and immunological transformation. The nanocoating masks immune ligands and maintains a mechanically stiff, quiescent state during circulation, while the tumor microenvironment removes the armor and restores cellular deformability and immune accessibility.
Zhao Guo +9 more
wiley +1 more source
IEEE Access, 2018 Deep convolutional neural networks (DCNNs) have been driving significant advances in semantic image segmentation due to their powerful feature representation for recognition.
Liang Zhang +7 more
doaj +1 more source
Advanced Optical Materials, EarlyView.Disordered plasmonic metasurfaces enable advanced control over light scattering through disorder engineering. A theoretical model based on multiple scattering theory is developed to predict the coherent reflection and transmission of light from disordered metasurfaces with arbitrary pair correlations.
Jialin Hu, Kevin Vynck
wiley +1 more source
IEEE Access, 2021 Weaponry equipment names belong to an important military naming entity that is difficult to identify because of features, such as complex components, miscellaneous, and scarce annotation corpus. Here, the automatic recognition of weaponry equipment names
Chenguang Liu +3 more
doaj +1 more source
Learning in Markov Random Fields with Contrastive Free Energies [PDF]
, 2005 Learning Markov random field (MRF) models is notoriously hard due to the presence of a global normalization factor. In this paper we present a new framework for learning MRF models based on the contrastive free energy (CF) objective function.
Welling, Max +3 more
core
NadaAbrg/binary-random-field: release 1
, 2023 <p>generate binary random field in MatLab</p ...
NadaAbrg
core +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source