Identification of Leaf Disease Based on Memristor Convolutional Neural Networks
IEEE AccessDeep learning methods based on convolutional neural networks can identify subtle disease features in plant leaves, thereby improving the accuracy and efficiency of plant leaf disease detection.
Nengyuan Pan +3 more
doaj +1 more source
Automated liver lesion detection in 68Ga DOTATATE PET/CT using a deep fully convolutional neural network. [PDF]
EJNMMI Res, 2021 Wehrend J, Silosky M, Xing F, Chin BB.
europepmc +1 more source
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
Advanced Science, EarlyView.ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source
Reverberation Noise Suppression in Ultrasound Channel Signals Using a 3D Fully Convolutional Neural Network. [PDF]
IEEE Trans Med Imaging, 2021 Brickson LL +3 more
europepmc +1 more source
Advanced Science, EarlyView.Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas +6 more
wiley +1 more source
Atmospheric Turbulence Intensity Image Acquisition Method Based on Convolutional Neural Network
Remote SensingAn algorithmic model of a neural network with channel attention and spatial attention (CASANet) is proposed to estimate the value of atmospheric coherence length, which in turn provides a quantitative description of atmospheric turbulence intensity.
Yuan Mu +6 more
doaj +1 more source
Fast super-resolution ultrasound microvessel imaging using spatiotemporal data with deep fully convolutional neural network. [PDF]
Phys Med Biol, 2021 Lok UW +12 more
europepmc +1 more source
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Time-series modeling with undecimated fully convolutional neural networks
CoRR, 2015 We present a new convolutional neural network-based time-series model. Typical convolutional neural network (CNN) architectures rely on the use of max-pooling operators in between layers, which leads to reduced resolution at the top layers. Instead, in this work we consider a fully convolutional network (FCN) architecture that uses causal filtering ...
openaire +2 more sources
Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers
Advanced Science, EarlyView.FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao +9 more
wiley +1 more source