AIMC Topic: Neural Networks, Computer

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A non-destructive methodology for determination of cantaloupe sugar content using machine vision and deep learning.

Journal of the science of food and agriculture
BACKGROUND: To determine the maturity of cantaloupe, measuring the soluble solid content (SSC) as the indicator of sugar content based on the refractometric index is commonly practised. This method, however, is destructive and limited to a small numb...

A parallel network utilizing local features and global representations for segmentation of surgical instruments.

International journal of computer assisted radiology and surgery
PURPOSE: Automatic image segmentation of surgical instruments is a fundamental task in robot-assisted minimally invasive surgery, which greatly improves the context awareness of surgeons during the operation. A novel method based on Mask R-CNN is pro...

Neural network interpolation operators optimized by Lagrange polynomial.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce a new type of interpolation operators by using Lagrange polynomials of degree r, which can be regarded as feedforward neural networks with four layers. The approximation rate of the new operators can be estimated by the (r...

A new predefined-time stability theorem and its application in the synchronization of memristive complex-valued BAM neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, two novel and general predefined-time stability lemmas are given and applied to the predefined-time synchronization problem of memristive complex-valued bidirectional associative memory neural networks (MCVBAMNNs). Firstly, different f...

Machine learning for contour classification in TG-263 noncompliant databases.

Journal of applied clinical medical physics
A large volume of medical data are labeled using nonstandardized nomenclature. Although efforts have been made by the American Association of Physicists in Medicine (AAPM) to standardize nomenclature through Task Group 263 (TG-263), there remain nonc...

Deep Neural Networks Applied to Stock Market Sentiment Analysis.

Sensors (Basel, Switzerland)
The volume of data is growing exponentially and becoming more valuable to organizations that collect it, from e-commerce data, shipping, audio and video logs, text messages, internet search queries, stock market activity, financial transactions, the ...

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...

Inspection of Underwater Hull Surface Condition Using the Soft Voting Ensemble of the Transfer-Learned Models.

Sensors (Basel, Switzerland)
In this study, we propose a method for inspecting the condition of hull surfaces using underwater images acquired from the camera of a remotely controlled underwater vehicle (ROUV). To this end, a soft voting ensemble classifier comprising six well-k...

Multi-type feature fusion based on graph neural network for drug-drug interaction prediction.

BMC bioinformatics
BACKGROUND: Drug-Drug interactions (DDIs) are a challenging problem in drug research. Drug combination therapy is an effective solution to treat diseases, but it can also cause serious side effects. Therefore, DDIs prediction is critical in pharmacol...

Maximum entropy models provide functional connectivity estimates in neural networks.

Scientific reports
Tools to estimate brain connectivity offer the potential to enhance our understanding of brain functioning. The behavior of neuronal networks, including functional connectivity and induced connectivity changes by external stimuli, can be studied usin...