AIMC Topic: Software

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tension: A Python package for FORCE learning.

PLoS computational biology
First-Order, Reduced and Controlled Error (FORCE) learning and its variants are widely used to train chaotic recurrent neural networks (RNNs), and outperform gradient methods on certain tasks. However, there is currently no standard software framewor...

Calligraphy and Painting Identification 3D-CNN Model Based on Hyperspectral Image MNF Dimensionality Reduction.

Computational intelligence and neuroscience
As a kind of cultural art, calligraphy and painting are not only an important part of traditional culture but also has important value of art collection and trade. The existence of forgeries has seriously affected the fair trade, protection, and inhe...

Visual Comparison of Language Model Adaptation.

IEEE transactions on visualization and computer graphics
Neural language models are widely used; however, their model parameters often need to be adapted to the specific domains and tasks of an application, which is time- and resource-consuming. Thus, adapters have recently been introduced as a lightweight...

Machine learning computational tools to assist the performance of systematic reviews: A mapping review.

BMC medical research methodology
BACKGROUND: Within evidence-based practice (EBP), systematic reviews (SR) are considered the highest level of evidence in that they summarize the best available research and describe the progress in a determined field. Due its methodology, SR require...

Operon Finder: A Deep Learning-based Web Server for Accurate Prediction of Prokaryotic Operons.

Journal of molecular biology
Operons are groups of consecutive genes that transcribe together under the regulation of a common promoter. They influence protein regulation and various physiological pathways, making their accurate detection desirable. The detection of operons thro...

Early stopping by correlating online indicators in neural networks.

Neural networks : the official journal of the International Neural Network Society
In order to minimize the generalization error in neural networks, a novel technique to identify overfitting phenomena when training the learner is formally introduced. This enables support of a reliable and trustworthy early stopping condition, thus ...

Robot-assisted subretinal injection system: development and preliminary verification.

BMC ophthalmology
BACKGROUND: To design and develop a surgical robot capable of assisting subretinal injection.

DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data.

BMC bioinformatics
BACKGROUND: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE suffers from transcriptional an...

Prospective risk analysis of the online-adaptive artificial intelligence-driven workflow using the Ethos treatment system.

Zeitschrift fur medizinische Physik
PURPOSE: The recently introduced Varian Ethos system allows adjusting radiotherapy treatment plans to anatomical changes on a daily basis. The system uses artificial intelligence to speed up the process of creating adapted plans, comes with its own s...

Non-fragile output-feedback synchronization for delayed discrete-time complex-valued neural networks with randomly occurring uncertainties.

Neural networks : the official journal of the International Neural Network Society
This paper is step forward to establish an exponential synchronization criterion for discrete-time complex-valued neural networks (CVNNs) having time-varying delays subject to randomly occurring uncertain weighting parameters, in order to overcome th...