AIMC Topic: Neural Networks, Computer

Clear Filters Showing 8421 to 8430 of 31376 articles

Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model.

Journal of visualized experiments : JoVE
Trypanosomiasis is a significant public health problem in several regions across the world, including South Asia and Southeast Asia. The identification of hotspot areas under active surveillance is a fundamental procedure for controlling disease tran...

Detection of Ponzi scheme on Ethereum using machine learning algorithms.

Scientific reports
Security threats posed by Ponzi schemes present a considerably higher risk compared to many other online crimes. These fraudulent online businesses, including Ponzi schemes, have witnessed rapid growth and emerged as major threats in societies like N...

Recognition and reconstruction of cell differentiation patterns with deep learning.

PLoS computational biology
Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to rep...

SpheroScan: a user-friendly deep learning tool for spheroid image analysis.

GigaScience
BACKGROUND: In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has...

Feature recognition in multiple CNNs using sEMG images from a prototype comfort test.

Computer methods and programs in biomedicine
OBJECTIVE: Deep learning-based CNN networks have recently been investigated to solve the problem of body posture recognition based on surface electromyographic signals (sEMG). Influenced by these studies, to develop a combined approach of sEMG and CN...

Multi-scale feature selection network for lightweight image super-resolution.

Neural networks : the official journal of the International Neural Network Society
Recently, many super-resolution (SR) methods based on convolutional neural networks (CNNs) have achieved superior performance by utilizing deep and heavy models, which may not be suitable for real-world low-budget devices. To address this issue, we p...

Heterogeneous context interaction network for vehicle re-identification.

Neural networks : the official journal of the International Neural Network Society
Capturing global and subtle discriminative information using attention mechanisms is essential to address the challenge of inter-class high similarity for vehicle re-identification (Re-ID) task. Mixing self-information of nodes or modeling context ba...

Improving model robustness of traffic crash risk evaluation via adversarial mix-up under traffic flow fundamental diagram.

Accident; analysis and prevention
Recent state-of-art crash risk evaluation studies have exploited deep learning (DL) techniques to improve performance in identifying high-risk traffic operation statuses. However, it is doubtful if such DL-based models would remain robust to real-wor...

Bayesian parametric models for survival prediction in medical applications.

BMC medical research methodology
BACKGROUND: Evidence-based treatment decisions in medicine are made founded on population-level evidence obtained during randomized clinical trials. In an era of personalized medicine, these decisions should be based on the predicted benefit of a tre...

Bacterial colony size growth estimation by deep learning.

BMC microbiology
The bacterial growth rate is important for pathogenicity and food safety. Therefore, the study of bacterial growth rate over time can provide important data from a medical and veterinary point of view. We trained convolutional neural networks (CNNs) ...