AIMC Topic: Neural Networks, Computer

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Feature discretization-based deep clustering for thyroid ultrasound image feature extraction.

Computers in biology and medicine
Ultrasound imaging technology has the advantage of being convenient, less harmful and widely applied, making ultrasonography one of the most popular methods for disease diagnosis. With the rapid development of Computer- Aided Diagnosis (CAD) technolo...

On the Frustration to Predict Binding Affinities from Protein-Ligand Structures with Deep Neural Networks.

Journal of medicinal chemistry
Accurate prediction of binding affinities from protein-ligand atomic coordinates remains a major challenge in early stages of drug discovery. Using modular message passing graph neural networks describing both the ligand and the protein in their free...

Permutation-Invariant-Polynomial Neural-Network-Based Δ-Machine Learning Approach: A Case for the HO Self-Reaction and Its Dynamics Study.

The journal of physical chemistry letters
Δ-machine learning, or the hierarchical construction scheme, is a highly cost-effective method, as only a small number of high-level energies are required to improve a potential energy surface (PES) fit to a large number of low-level points. However...

Accurate Step Count with Generalized and Personalized Deep Learning on Accelerometer Data.

Sensors (Basel, Switzerland)
Physical activity (PA) is globally recognized as a pillar of general health. Step count, as one measure of PA, is a well known predictor of long-term morbidity and mortality. Despite its popularity in consumer devices, a lack of methodological standa...

Resolving complex cartilage structures in developmental biology via deep learning-based automatic segmentation of X-ray computed microtomography images.

Scientific reports
The complex shape of embryonic cartilage represents a true challenge for phenotyping and basic understanding of skeletal development. X-ray computed microtomography (μCT) enables inspecting relevant tissues in all three dimensions; however, most 3D m...

Experimental implementation of a neural network optical channel equalizer in restricted hardware using pruning and quantization.

Scientific reports
The deployment of artificial neural networks-based optical channel equalizers on edge-computing devices is critically important for the next generation of optical communication systems. However, this is still a highly challenging problem, mainly due ...

Bayesian optimization and deep learning for steering wheel angle prediction.

Scientific reports
Automated driving systems (ADS) have undergone a significant improvement in the last years. ADS and more precisely self-driving cars technologies will change the way we perceive and know the world of transportation systems in terms of user experience...

The Application of Pattern Recognition System in Design Field Based on Aesthetic Principles.

Computational intelligence and neuroscience
The design system based on aesthetic principles is the most representative in the field of design and has a certain significance for the research and construction of design aesthetics and the development of design education. Therefore, this paper stu...

A Novel Genetic Neural Network Algorithm with Link Switches and Its Application in University Professional Course Evaluation.

Computational intelligence and neuroscience
This study exploits a novel enhanced genetic neural network algorithm with link switches (EGA-NNLS) to model the professional university course evaluating system. Various indices should be employed to evaluate the learning effect of a professional co...

Detection of Peripheral Malarial Parasites in Blood Smears Using Deep Learning Models.

Computational intelligence and neuroscience
Due to the plasmodium parasite, malaria is transmitted mostly through red blood cells. Manually counting blood cells is extremely time consuming and tedious. In a recommendation for the advanced technology stage and analysis of malarial disease, the ...