Results 71 to 80 of about 324,009 (309)

A self‐supervised causal feature reinforcement learning method for non‐invasive hemoglobin prediction

IET Image Processing
Anemia (hemoglobin (Hb) 
Linquan Xu, Yuwen Chen, Songmei Lu, Kunhua Zhong, Yujie Li, Bin Yi   +5 more
doaj   +1 more source

Carbon Nanotube 3D Integrated Circuits: From Design to Applications

Advanced Functional Materials, EarlyView.
As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu, Yun Sun, Dong‐Ming Sun, Hui‐Ming Cheng   +3 more
wiley   +1 more source

Real‐time vehicle detection using segmentation‐based detection network and trajectory prediction

IET Computer Vision
The position of vehicles is determined using an algorithm that includes two stages of detection and prediction. The more the number of frames in which the detection network is used, the more accurate the detector is, and the more the prediction network ...
Nafiseh Zarei, Payman Moallem, Mohammadreza Shams   +2 more
doaj   +1 more source

Initial condition based real time classification of power quality disturbance using deep convolution neural network with bidirectional long short‐term memory

IET Generation, Transmission & Distribution, 2023
The accurate classification of power quality disturbances (PQDs) is crucial for advancing real‐time monitoring and classification systems within the modern power grid.
Prabaakaran Kandasamy, Chandrasekaran Kumar, Muthuramalingam Lakshmanan, Selvaraj Jaisiva, Albert Alexander Stonier, Geno Peter, Vivekananda Ganji   +6 more
doaj   +1 more source

Improving neural networks by preventing co-adaptation of feature detectors [PDF]

, 2012
When a large feedforward neural network is trained on a small training set, it typically performs poorly on held-out test data. This "overfitting" is greatly reduced by randomly omitting half of the feature detectors on each training case.
Hinton, Geoffrey E., Krizhevsky, Alex, Salakhutdinov, Ruslan R., Srivastava, Nitish, Sutskever, Ilya   +4 more
core   +1 more source

Deep Expander Networks: Efficient Deep Networks from Graph Theory

, 2018
Efficient CNN designs like ResNets and DenseNet were proposed to improve accuracy vs efficiency trade-offs. They essentially increased the connectivity, allowing efficient information flow across layers.
H Zhou, K He, M Masana, M Rastegari, S Hoory, S Scardapane, SP Vadhan   +6 more
core   +1 more source

Autonomous Control of Extrusion Bioprinting Using Convolutional Neural Networks

Advanced Functional Materials, EarlyView.
This work presents a novel computer vision system for high‐fidelity monitoring of extrusion‐based bioprinting and a correction system utilizing convolutional neural networks for error mitigation. This system has demonstrated high detection accuracy and extrusion correction abilities that advance the state of the art toward accelerated printing ...
Daniel Kelly, Vasileios Sergis, Laura Ventura i Blanco, Karl Mason, Andrew C. Daly   +4 more
wiley   +1 more source

Deep Fishing: Gradient Features from Deep Nets

, 2015
Convolutional Networks (ConvNets) have recently improved image recognition performance thanks to end-to-end learning of deep feed-forward models from raw pixels.
Gaidon, Adrien, Gordo, Albert, Perronnin, Florent   +2 more
core   +1 more source

Printing Nacre‐Mimetic MXene‐Based E‐Textile Devices for Sensing and Breathing‐Pattern Recognition Using Machine Learning

Advanced Functional Materials, EarlyView.
This study presents a Ti3C2Tx MXene/WPU nacre‐mimetic nanomaterial as a printable ink for direct‐write printing onto textiles‐based sensors. The resulting wearable device demonstrates high sensitivity, biocompatibility, and mechanical strength. Furthermore, NFC‐enabled humidity sensor produces time‐series data, which informs a machine learning ...
Lulu Xu, Wenqing Chen, Qian Li, Rohit Gupta, Biswajoy Bagchi, Laurence B. Lovat, Manish K. Tiwari   +6 more
wiley   +1 more source

A fast direct locator for radiation source based on composite convolution neural network

Electronics Letters
The high spatial search complexity of the direct positioning method in passive positioning systems leads to long positioning time and high computational resource consumption.
Chenhao Gong, Guomei Zhang, Guobing Li, Yue Mao   +3 more
doaj   +1 more source