AIMC Topic: Neural Networks, Computer

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Sea Cucumber Detection Algorithm Based on Deep Learning.

Sensors (Basel, Switzerland)
The traditional single-shot multiBox detector (SSD) for the recognition process in sea cucumbers has problems, such as an insufficient expression of features, heavy computation, and difficulty in application to embedded platforms. To solve these prob...

CSatDTA: Prediction of Drug-Target Binding Affinity Using Convolution Model with Self-Attention.

International journal of molecular sciences
Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug-target affinity is crucial. The pr...

Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms.

Scientific reports
Evaporation is the primary aspect causing water loss in the hydrological cycle; therefore, water loss must be precisely measured. Evaporation is an intricate nonlinear process occurring as a result of several climatic aspects. The purpose of this res...

Robust prediction of force chains in jammed solids using graph neural networks.

Nature communications
Force chains are quasi-linear self-organised structures carrying large stresses and are ubiquitous in jammed amorphous materials like granular materials, foams or even cell assemblies. Predicting where they will form upon deformation is crucial to de...

Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images.

BMC medical imaging
BACKGROUND: Corona Virus Disease 2019 (COVID-19) first appeared in December 2019, and spread rapidly around the world. COVID-19 is a pneumonia caused by novel coronavirus infection in 2019. COVID-19 is highly infectious and transmissible. By 7 May 20...

Detection of Pneumonia Infection by Using Deep Learning on a Mobile Platform.

Computational intelligence and neuroscience
Pneumonia is a disease that spreads quickly and poses a serious risk to the health and well-being of its victims. An accurate biomedical diagnosis of pneumonia necessitates the use of various diagnostic tools and the evaluation of various clinical fe...

Research on Blended Teaching of Flipped Classroom Based on CNN-SSA-Bi-LSTM Deep Learning Model Computer Media.

Computational intelligence and neuroscience
Aiming at the problem that the influencing factors of computer media flipped classroom hybrid teaching lead to the teaching effect not reaching the expected, this study proposes an ultra-short-term prediction model based on CNN-SSA-Bi-LSTM. CNN-SSA-B...

Optimization of Ideological and Political Education Strategies in Colleges and Universities Based on Deep Learning.

Computational intelligence and neuroscience
In the current technological world, artificially intelligent deep learning techniques are adapted in many fields. This advanced technology is also used in the field of education. In this study, people will conduct research on the optimization of ideo...

Artificial Intelligence-Based Feature Analysis of Ultrasound Images of Liver Fibrosis.

Computational intelligence and neuroscience
Liver fibrosis is a common liver disease that seriously endangers human health. Liver biopsy is the gold standard for diagnosing liver fibrosis, but its clinical use is limited due to its invasive nature. Ultrasound image examination is a widely used...

Deep Learning Scoring Model in the Evaluation of Oral English Teaching.

Computational intelligence and neuroscience
This study is aimed at improving the accuracy of oral English recognition and proposing evaluation measures with better performance. This work is based on related theories such as deep learning, speech recognition, and oral English practice. As the l...