AIMC Topic: Neural Networks, Computer

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In-line near-infrared analysis of milk coupled with machine learning methods for the daily prediction of blood metabolic profile in dairy cattle.

Scientific reports
Precision livestock farming technologies are used to monitor animal health and welfare parameters continuously and in real time in order to optimize nutrition and productivity and to detect health issues at an early stage. The possibility of predicti...

Two-Stream Retentive Long Short-Term Memory Network for Dense Action Anticipation.

Computational intelligence and neuroscience
Analyzing and understanding human actions in long-range videos has promising applications, such as video surveillance, automatic driving, and efficient human-computer interaction. Most researches focus on short-range videos that predict a single acti...

TagSeq: Malicious behavior discovery using dynamic analysis.

PloS one
In recent years, studies on malware analysis have noticeably increased in the cybersecurity community. Most recent studies concentrate on malware classification and detection or malicious patterns identification, but as to malware activity, it still ...

Leak detection in real water distribution networks based on acoustic emission and machine learning.

Environmental technology
Water scarcity as well as social and economic damages caused by the increasing amounts of non-revenue water in the water distribution networks (WDNs) have been prompting innovative solutions. A great deal of potable water is wasted due to leakage in ...

Fast Analysis of Time-Domain Fluorescence Lifetime Imaging via Extreme Learning Machine.

Sensors (Basel, Switzerland)
We present a fast and accurate analytical method for fluorescence lifetime imaging microscopy (FLIM), using the extreme learning machine (ELM). We used extensive metrics to evaluate ELM and existing algorithms. First, we compared these algorithms usi...

The Effectiveness of Artificial Intelligence in Detection of Oral Cancer.

International dental journal
AIM: The early detection of oral cancer (OC) at the earliest stage significantly increases survival rates. Recently, there has been an increasing interest in the use of artificial intelligence (AI) technologies in diagnostic medicine. This study aime...

Nucleus classification in histology images using message passing network.

Medical image analysis
Identification of nuclear components in the histology landscape is an important step towards developing computational pathology tools for the profiling of tumor micro-environment. Most existing methods for the identification of such components are li...

Algal bloom forecasting with time-frequency analysis: A hybrid deep learning approach.

Water research
The rapid emergence of deep learning long-short-term-memory (LSTM) technique presents a promising solution to algal bloom forecasting. However, the discontinuous and non-stationary processes within algal dynamics still largely limit the functions of ...

Effective high-to-low-level feature aggregation network for endoscopic image classification.

International journal of computer assisted radiology and surgery
PURPOSE: The accuracy improvement in endoscopic image classification matters to the endoscopists in diagnosing and choosing suitable treatment for patients. Existing CNN-based methods for endoscopic image classification tend to use the deepest abstra...

2D-DOA Estimation in Switching UCA Using Deep Learning-Based Covariance Matrix Completion.

Sensors (Basel, Switzerland)
In this paper, we study the two-dimensional direction of arrival (2D-DOA) estimation problem in a switching uniform circular array (SUCA), which means performing 2D-DOA estimation with a reduction in the number of radio frequency (RF) chains. We prop...