AIMC Topic: Neural Networks, Computer

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Deep embeddings and logistic regression for rapid active learning in histopathological images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Recognizing different tissue components is one of the most fundamental and essential works in digital pathology. Current methods are often based on convolutional neural networks (CNNs), which need numerous annotated samples ...

Structural Response Prediction for Damage Identification Using Wavelet Spectra in Convolutional Neural Network.

Sensors (Basel, Switzerland)
If damage to a building caused by an earthquake is not detected immediately, the opportunity to decide on quick action, such as evacuating the building, is lost. For this reason, it is necessary to develop modern technologies that can quickly obtain ...

Dynamics and Control of a Magnetic Transducer Array Using Multi-Physics Models and Artificial Neural Networks.

Sensors (Basel, Switzerland)
A linear mechanical oscillator is non-linearly coupled with an electromagnet and its driving circuit through a magnetic field. The resulting non-linear dynamics are investigated using magnetic circuit approximations without major loss of accuracy and...

Real-Time Detection of Non-Stationary Objects Using Intensity Data in Automotive LiDAR SLAM.

Sensors (Basel, Switzerland)
This article aims at demonstrating the feasibility of modern deep learning techniques for the real-time detection of non-stationary objects in point clouds obtained from 3-D light detecting and ranging (LiDAR) sensors. The motion segmentation task is...

Session Recommendation Model Based on Context-Aware and Gated Graph Neural Networks.

Computational intelligence and neuroscience
The graph neural network (GNN) based approach has been successfully applied to session-based recommendation tasks. However, in the face of complex and changing real-world situations, the existing session recommendation algorithms do not fully conside...

A Method for Short-Term Prediction of the Metro Station's Individual Energy Consumption Item Based on G-ACO-BP Model.

Computational intelligence and neuroscience
This paper proposes a new method to make short-term predictions for the three kinds of primary energy consumption of power, lighting, and ventilated air conditioning in the metro station. First, the paper extracts the five main factors influencing me...

Anti-cancer Peptide Recognition Based on Grouped Sequence and Spatial Dimension Integrated Networks.

Interdisciplinary sciences, computational life sciences
The diversification of the characteristic sequences of anti-cancer peptides has imposed difficulties on research. To effectively predict new anti-cancer peptides, this paper proposes a more suitable feature grouping sequence and spatial dimension-int...

CT classification model of pancreatic serous cystic neoplasms and mucinous cystic neoplasms based on a deep neural network.

Abdominal radiology (New York)
BACKGROUND: At present, numerous challenges exist in the diagnosis of pancreatic SCNs and MCNs. After the emergence of artificial intelligence (AI), many radiomics research methods have been applied to the identification of pancreatic SCNs and MCNs.

BCHisto-Net: Breast histopathological image classification by global and local feature aggregation.

Artificial intelligence in medicine
Breast cancer among women is the second most common cancer worldwide. Non-invasive techniques such as mammograms and ultrasound imaging are used to detect the tumor. However, breast histopathological image analysis is inevitable for the detection of ...