AIMC Topic: Neural Networks, Computer

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Construction and Application Research of the Visual Image Obstacle Type Recognition Model Based on the Computer-Expanded Convolutional Neural Network.

Computational intelligence and neuroscience
Due to the development of computer vision technology and image processing technology, obstacle recognition technology has been widely used in military and scientific research fields. However, most of the existing image-based recognition technologies ...

University Archives Autonomous Management Control System under the Internet of Things and Deep Learning Professional Certification.

Computational intelligence and neuroscience
The current work aims to meet the needs of the development of archives work in colleges and universities and the modernization of management to realize the standards and standardization of all aspects of archives business construction in colleges and...

Predictive Control of the Mobile Robot under the Deep Long-Short Term Memory Neural Network Model.

Computational intelligence and neuroscience
At present, there is a phenomenon of network data packet loss in the trajectory tracking control system, which will degrade or even destabilize the system's performance. Therefore, this work first explains the theory of the deep long-short term memor...

Machine English Translation Evaluation System Based on BP Neural Network Algorithm.

Computational intelligence and neuroscience
In order to solve the problems of machine translation efficiency and translation quality, this paper proposes an English translation evaluation system based on the BP neural network algorithm. This method provides users with a more intelligent machin...

Intelligent Detection and Diagnosis of Power Failure Relying on BP Neural Network Algorithm.

Computational intelligence and neuroscience
The development of economy and the needs of urban planning have led to the rapid growth of power applications and the corresponding frequent occurrence of power failures, which many times lead to a series of economic losses due to failure to repair i...

Ensemble Dilated Convolutional Neural Network and Its Application in Rotating Machinery Fault Diagnosis.

Computational intelligence and neuroscience
Fault diagnosis of rotating machinery is an attractive yet challenging task. This paper presents a novel intelligent fault diagnosis scheme for rotating machinery based on ensemble dilated convolutional neural networks. The novel fault diagnosis fram...

A Deep Spiking Neural Network Anomaly Detection Method.

Computational intelligence and neuroscience
Cyber-attacks on specialized industrial control systems are increasing in frequency and sophistication, which means stronger countermeasures need to be implemented, requiring the designers of the equipment in question to re-evaluate and redefine thei...

Predicting Substance Use Treatment Failure with Transfer Learning.

Substance use & misuse
Transfer learning, which involves repurposing a trained model on a related task, may allow for better predictions with substance use data than models that are trained using the target data alone. This approach may also be useful for small clinical da...

Transfer Learning Approach and Nucleus Segmentation with MedCLNet Colon Cancer Database.

Journal of digital imaging
Machine learning has been recently used especially in the medical field. In the diagnosis of serious diseases such as cancer, deep learning techniques can be used to reduce the workload of experts and to produce quick solutions. The nuclei found in t...

DEFEAT: Decoupled feature attack across deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Adversarial attacks pose a security challenge for deep neural networks, motivating researchers to build various defense methods. Consequently, the performance of black-box attacks turns down under defense scenarios. A significant observation is that ...