AIMC Topic: Neural Networks, Computer

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A memristive all-inclusive hypernetwork for parallel analog deployment of full search space architectures.

Neural networks : the official journal of the International Neural Network Society
In recent years, there has been a significant advancement in memristor-based neural networks, positioning them as a pivotal processing-in-memory deployment architecture for a wide array of deep learning applications. Within this realm of progress, th...

Unsupervised Sentence Representation Learning with Frequency-induced Adversarial tuning and Incomplete sentence filtering.

Neural networks : the official journal of the International Neural Network Society
Pre-trained Language Model (PLM) is nowadays the mainstay of Unsupervised Sentence Representation Learning (USRL). However, PLMs are sensitive to the frequency information of words from their pre-training corpora, resulting in anisotropic embedding s...

DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images.

Magnetic resonance imaging
BACKGROUND AND PURPOSE: Higher magnetic field strength introduces stronger magnetic field inhomogeneities in the brain, especially within temporal lobes, leading to image artifacts. Particularly, T2-weighted fluid-attenuated inversion recovery (FLAIR...

Brain tumor detection using proper orthogonal decomposition integrated with deep learning networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The central organ of the human nervous system is the brain, which receives and sends stimuli to the various parts of the body to engage in daily activities. Uncontrolled growth of brain cells can result in tumors which affec...

Tumor Segmentation in Intraoperative Fluorescence Images Based on Transfer Learning and Convolutional Neural Networks.

Surgical innovation
OBJECTIVE: To propose a transfer learning based method of tumor segmentation in intraoperative fluorescence images, which will assist surgeons to efficiently and accurately identify the boundary of tumors of interest.

PT-Finder: A multi-modal neural network approach to target identification.

Computers in biology and medicine
Efficient target identification for bioactive compounds, including novel synthetic analogs, is crucial for accelerating the drug discovery pipeline. However, the process of target identification presents significant challenges and is often expensive,...

Machine-Learning-Assisted Aggregation-Induced Emissive Nanosilicon-Based Sensor Array for Point-of-Care Identification of Multiple Foodborne Pathogens.

Analytical chemistry
How timely identification and determination of pathogen species in pathogen-contaminated foods are responsible for rapid and accurate treatments for food safety accidents. Herein, we synthesize four aggregation-induced emissive nanosilicons with diff...

Optimisation and Calibration of Bayesian Neural Network for Probabilistic Prediction of Biogas Performance in an Anaerobic Lagoon.

Sensors (Basel, Switzerland)
This study aims to enhance diagnostic capabilities for optimising the performance of the anaerobic sewage treatment lagoon at Melbourne Water's Western Treatment Plant (WTP) through a novel machine learning (ML)-based monitoring strategy. This strate...

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data.

Sensors (Basel, Switzerland)
Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user's quality of life and safety, a...

Identification of agricultural surface source pollution in plain river network areas based on 3D-EEMs and convolutional neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
Agricultural non-point sources, as major sources of organic pollution, continue to flow into the river network area of the Jiangnan Plain, posing a serious threat to the quality of water bodies, the ecological environment, and human health. Therefore...