AIMC Topic: Algorithms

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Hybrid Improved Bird Swarm Algorithm with Extreme Learning Machine for Short-Term Power Prediction in Photovoltaic Power Generation System.

Computational intelligence and neuroscience
When a photovoltaic (PV) system is connected to the electric power grid, the power system reliability may be exposed to a threat due to its inherent randomness and volatility. Consequently, predicting PV power generation becomes necessary for reasona...

Multi- class classification of breast cancer abnormalities using Deep Convolutional Neural Network (CNN).

PloS one
The real cause of breast cancer is very challenging to determine and therefore early detection of the disease is necessary for reducing the death rate due to risks of breast cancer. Early detection of cancer boosts increasing the survival chance up t...

Rosetta:MSF:NN: Boosting performance of multi-state computational protein design with a neural network.

PloS one
Rational protein design aims at the targeted modification of existing proteins. To reach this goal, software suites like Rosetta propose sequences to introduce the desired properties. Challenging design problems necessitate the representation of a pr...

Characterizing and forecasting the responses of tropical forest leaf phenology to El Nino by machine learning algorithms.

PloS one
Climate change and global warming have serious adverse impacts on tropical forests. In particular, climate change may induce changes in leaf phenology. However, in tropical dry forests where tree diversity is high, species responses to climate change...

Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.

PloS one
BACKGROUND: Linked color imaging (LCI) has been shown to be effective in multiple randomized controlled trials for enhanced colorectal polyp detection. Recently, artificial intelligence (AI) with deep learning through convolutional neural networks ha...

Radiomics: a primer on high-throughput image phenotyping.

Abdominal radiology (New York)
Radiomics is a high-throughput approach to image phenotyping. It uses computer algorithms to extract and analyze a large number of quantitative features from radiological images. These radiomic features collectively describe unique patterns that can ...

Adversarial parameter defense by multi-step risk minimization.

Neural networks : the official journal of the International Neural Network Society
Previous studies demonstrate DNNs' vulnerability to adversarial examples and adversarial training can establish a defense to adversarial examples. In addition, recent studies show that deep neural networks also exhibit vulnerability to parameter corr...

Automatic annotation of cervical vertebrae in videofluoroscopy images via deep learning.

Medical image analysis
Judging swallowing kinematic impairments via videofluoroscopy represents the gold standard for the detection and evaluation of swallowing disorders. However, the efficiency and accuracy of such a biomechanical kinematic analysis vary significantly am...

Automatic registration and precise tumour localization method for robot-assisted puncture procedure under inconsistent breath-holding conditions.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: During percutaneous puncture procedure, breath holding is subjectively controlled by patients, and it is difficult to ensure consistent tumour position between the preoperative CT scanning phase and the intraoperative puncture phase. In a...

Deep learning in forensic shotgun pattern interpretation - A proof-of-concept study.

Legal medicine (Tokyo, Japan)
Little is known about the potential of artificial intelligence in forensic shotgun pattern interpretation. As shooting distance is among the main factors behind shotgun patterning, this proof-of-concept study aimed to explore the potential of neural ...