AIMC Topic: Neural Networks, Computer

Clear Filters Showing 12931 to 12940 of 31376 articles

Learning Proteome Domain Folding Using LSTMs in an Empirical Kernel Space.

Journal of molecular biology
The recognition of protein structural folds is the starting point for protein function inference and for many structural prediction tools. We previously introduced the idea of using empirical comparisons to create a data-augmented feature space calle...

Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency.

Medical image analysis
Despite that Convolutional Neural Networks (CNNs) have achieved promising performance in many medical image segmentation tasks, they rely on a large set of labeled images for training, which is expensive and time-consuming to acquire. Semi-supervised...

Improving the robustness and accuracy of biomedical language models through adversarial training.

Journal of biomedical informatics
Deep transformer neural network models have improved the predictive accuracy of intelligent text processing systems in the biomedical domain. They have obtained state-of-the-art performance scores on a wide variety of biomedical and clinical Natural ...

Adapting a low-count acquisition of the bone scintigraphy using deep denoising super-resolution convolutional neural network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Deep-layer learning processing may improve contrast imaging with greater precision in low-count acquisition. However, no data on noise reduction using super-resolution processing for deep-layer learning have been reported in nuclear medicine...

Sequential Properties Representation Scheme for Recurrent Neural Network-Based Prediction of Therapeutic Peptides.

Journal of chemical information and modeling
The discovery of therapeutic peptides is often accelerated by means of virtual screening supported by machine learning-based predictive models. The predictive performance of such models is sensitive to the choice of data and its representation scheme...

Neuromorphic computing chip with spatiotemporal elasticity for multi-intelligent-tasking robots.

Science robotics
Recent advances in artificial intelligence have enhanced the abilities of mobile robots in dealing with complex and dynamic scenarios. However, to enable computationally intensive algorithms to be executed locally in multitask robots with low latency...

Simulation study on 3D convolutional neural networks for time-of-flight prediction in monolithic PET detectors using digitized waveforms.

Physics in medicine and biology
We investigate the use of 3D convolutional neural networks for gamma arrival time estimation in monolithic scintillation detectors.The required data is obtained by Monte Carlo simulation in GATE v8.2, based on a 50 × 50 × 16 mmmonolithic LYSO crystal...

Multi-class retinal fluid joint segmentation based on cascaded convolutional neural networks.

Physics in medicine and biology
. Retinal fluid mainly includes intra-retinal fluid (IRF), sub-retinal fluid (SRF) and pigment epithelial detachment (PED), whose accurate segmentation in optical coherence tomography (OCT) image is of great importance to the diagnosis and treatment ...

Speckle Noise Removal Model Based on Diffusion Equation and Convolutional Neural Network.

Computational intelligence and neuroscience
The image denoising model based on convolutional neural network (CNN) can achieve a good denoising effect. However, its robustness is poor, and it is not suitable for direct noise removal tasks. Differently, the image denoising method based on the di...

Lightweight Neural Networks-Based Safety Evaluation for Smart Construction Devices.

Computational intelligence and neuroscience
Based on the theory of lightweight neural networks, this paper presents a safety evaluation model for smart construction devices. The model index system includes the internal logical relationship between the input and output indexes, and the input in...