AIMC Topic: Algorithms

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Recognizing intertwined patterns using a network of spiking pattern recognition platforms.

Scientific reports
Artificial intelligence computing adapted from biology is a suitable platform for the development of intelligent machines by imitating the functional mechanisms of the nervous system in creating high-level activities such as learning, decision making...

Deep learning-based detection algorithm for brain metastases on black blood imaging.

Scientific reports
Brain metastases (BM) are the most common intracranial tumors, and their prevalence is increasing. High-resolution black-blood (BB) imaging was used to complement the conventional contrast-enhanced 3D gradient-echo imaging to detect BM. In this study...

Defending Person Detection Against Adversarial Patch Attack by Using Universal Defensive Frame.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person detection has attracted great attention in the computer vision area and is an imperative element in human-centric computer vision. Although the predictive performances of person detection networks have been improved dramatically, they are vuln...

A class of doubly stochastic shift operators for random graph signals and their boundedness.

Neural networks : the official journal of the International Neural Network Society
A class of doubly stochastic graph shift operators (GSO) is proposed, which is shown to exhibit: (i) lower and upper L-boundedness for locally stationary random graph signals, (ii) L-isometry for i.i.d. random graph signals with the asymptotic increa...

Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI.

European radiology
OBJECTIVES: Prostate volume (PV) in combination with prostate specific antigen (PSA) yields PSA density which is an increasingly important biomarker. Calculating PV from MRI is a time-consuming, radiologist-dependent task. The aim of this study was t...

The impact of artificial intelligence on radiography as a profession: A narrative review.

Journal of medical imaging and radiation sciences
BACKGROUND AND PURPOSE: Artificial intelligence (AI) algorithms, particularly deep learning, have made significant strides in image recognition and classification, providing remarkable diagnostic accuracy to various diseases. This domain of AI has be...

P-ResUnet: Segmentation of brain tissue with Purified Residual Unet.

Computers in biology and medicine
Brain tissue of Magnetic Resonance Imaging is precisely segmented and quantified, which aids in the diagnosis of neurological diseases such as epilepsy, Alzheimer's, and multiple sclerosis. Recently, UNet-like architectures are widely used for medica...

Application of classical and novel integrated machine learning models to predict sediment discharge during free-flow flushing.

Scientific reports
In this study, the capabilities of classical and novel integrated machine learning models were investigated to predict sediment discharge (Q) in free-flow flushing. Developed models include Multivariate Linear Regression (MLR), Artificial Neural Netw...

Bayesian Disturbance Injection: Robust imitation learning of flexible policies for robot manipulation.

Neural networks : the official journal of the International Neural Network Society
Humans demonstrate a variety of interesting behavioral characteristics when performing tasks, such as selecting between seemingly equivalent optimal actions, performing recovery actions when deviating from the optimal trajectory, or moderating action...

Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization.

European journal of radiology
PURPOSE: Extracting water equivalent diameter (DW), as a good descriptor of patient size, from the CT localizer before the spiral scan not only minimizes truncation errors due to the limited scan field-of-view but also enables prior size-specific dos...