AIMC Topic: Neural Networks, Computer

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Explainable deep transfer learning model for disease risk prediction using high-dimensional genomic data.

PLoS computational biology
Building an accurate disease risk prediction model is an essential step in the modern quest for precision medicine. While high-dimensional genomic data provides valuable data resources for the investigations of disease risk, their huge amount of nois...

A Machine Learning and Deep Learning Approach for Recognizing Handwritten Digits.

Computational intelligence and neuroscience
Optical character recognition (OCR) can be a subcategory of graphic design that involves extracting text from images or scanned documents. We have chosen to make unique handwritten digits available on the Modified National Institute of Standards and ...

Leveraging a Neuroevolutionary Approach for Classifying Violent Behavior in Video.

Computational intelligence and neuroscience
Security has become a critical issue for complex and expensive systems and day-to-day situations. In this regard, the analysis of surveillance cameras is a critical issue usually restricted to the number of people devoted to such a task, their knowle...

Medical Text Prediction and Suggestion Using Generative Pretrained Transformer Models with Dental Medical Notes.

Methods of information in medicine
BACKGROUND: Generative pretrained transformer (GPT) models are one of the latest large pretrained natural language processing models that enables model training with limited datasets and reduces dependency on large datasets, which are scarce and cost...

Exact mean-field models for spiking neural networks with adaptation.

Journal of computational neuroscience
Networks of spiking neurons with adaption have been shown to be able to reproduce a wide range of neural activities, including the emergent population bursting and spike synchrony that underpin brain disorders and normal function. Exact mean-field mo...

QMEDNet: A quaternion-based multi-order differential encoder-decoder model for 3D human motion prediction.

Neural networks : the official journal of the International Neural Network Society
In order to deal with the sequence information in the task of 3D human motion prediction effectively, many previous methods seek to predict the motion state of the next moment using the traditional recurrent neural network in Euclidean space. However...

Deep learning with multiresolution handcrafted features for brain MRI segmentation.

Artificial intelligence in medicine
The segmentation of magnetic resonance (MR) images is a crucial task for creating pseudo computed tomography (CT) images which are used to achieve positron emission tomography (PET) attenuation correction. One of the main challenges of creating pseud...

Single-shot retinal image enhancement using untrained and pretrained neural networks priors integrated with analytical image priors.

Computers in biology and medicine
Retinal images acquired using fundus cameras are often visually blurred due to imperfect imaging conditions, refractive medium turbidity, and motion blur. In addition, ocular diseases such as the presence of cataracts also result in blurred retinal i...

A Novel Memory and Time-Efficient ALPR System Based on YOLOv5.

Sensors (Basel, Switzerland)
With the rapid development of deep learning techniques, new innovative license plate recognition systems have gained considerable attention from researchers all over the world. These systems have numerous applications, such as law enforcement, parkin...

Application of Deep Reinforcement Learning to NS-SHAFT Game Signal Control.

Sensors (Basel, Switzerland)
Reinforcement learning (RL) with both exploration and exploit abilities is applied to games to demonstrate that it can surpass human performance. This paper mainly applies Deep Q-Network (DQN), which combines reinforcement learning and deep learning ...