AIMC Topic: Deep Learning

Clear Filters Showing 14731 to 14740 of 28423 articles

DXM-TransFuse U-net: Dual cross-modal transformer fusion U-net for automated nerve identification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate nerve identification is critical during surgical procedures to prevent damage to nerve tissues. Nerve injury can cause long-term adverse effects for patients, as well as financial overburden. Birefringence imaging is a noninvasive technique ...

DOC-IDS: A Deep Learning-Based Method for Feature Extraction and Anomaly Detection in Network Traffic.

Sensors (Basel, Switzerland)
With the growing diversity of cyberattacks in recent years, anomaly-based intrusion detection systems that can detect unknown attacks have attracted significant attention. Furthermore, a wide range of studies on anomaly detection using machine learni...

The Smart in Smart Cities: A Framework for Image Classification Using Deep Learning.

Sensors (Basel, Switzerland)
The need for a smart city is more pressing today due to the recent pandemic, lockouts, climate changes, population growth, and limitations on availability/access to natural resources. However, these challenges can be better faced with the utilization...

Application of the deep learning algorithm in nutrition research - using serum pyridoxal 5'-phosphate as an example.

Nutrition journal
BACKGROUND: Multivariable linear regression (MLR) models were previously used to predict serum pyridoxal 5'-phosphate (PLP) concentration, the active coenzyme form of vitamin B6, but with low predictability. We developed a deep learning algorithm (DL...

Using deep learning to detect digitally encoded DNA trigger for Trojan malware in Bio-Cyber attacks.

Scientific reports
This article uses Deep Learning technologies to safeguard DNA sequencing against Bio-Cyber attacks. We consider a hybrid attack scenario where the payload is encoded into a DNA sequence to activate a Trojan malware implanted in a software tool used i...

A deep learning approach for detecting drill bit failures from a small sound dataset.

Scientific reports
Monitoring the conditions of machines is vital in the manufacturing industry. Early detection of faulty components in machines for stopping and repairing the failed components can minimize the downtime of the machine. In this article, we present a me...

Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP.

Nature communications
The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user-friendly toolkit, BioNavi-NP, is developed to predict the biosynthet...

Deep learning for improving the spatial resolution of magnetic particle imaging.

Physics in medicine and biology
Magnetic particle imaging (MPI) is a new medical, non-destructive, imaging method for visualizing the spatial distribution of superparamagnetic iron oxide nanoparticles. In MPI, spatial resolution is an important indicator of efficiency; traditional ...

Personalized College English Learning Based on Deep Learning under the Background of Big Data.

Computational intelligence and neuroscience
Generally, in-depth learning has been extensively employed in numerous industries to enhance the growth of economic globalization since the dawn of the big data age. At the same time, the demand for foreign language talent has risen dramatically, and...

The Empirical Analysis of Bitcoin Price Prediction Based on Deep Learning Integration Method.

Computational intelligence and neuroscience
As a new type of electronic currency, bitcoin is more and more recognized and sought after by people, but its price fluctuation is more intense, the market has certain risks, and the price is difficult to be accurately predicted. The main purpose of ...