AIMC Topic: Neural Networks, Computer

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Temporomandibular joint CBCT image segmentation via multi-view ensemble learning network.

Medical & biological engineering & computing
Accurate segmentation of the temporomandibular joint (TMJ) from cone beam CT (CBCT) images holds significant clinical value for diagnosing temporomandibular joint osteoarthrosis (TMJOA) and related conditions. Convolutional neural network-based medic...

Multi-Class Segmentation Network Based on Tumor Tissue in Endometrial Cancer Pathology Images: ECMTrans-net.

The American journal of pathology
Endometrial cancer has the second highest incidence of malignant tumors in the female reproductive system. Accurate and efficient analysis of endometrial cancer pathology images is one of the important research components of computer-aided diagnosis....

Towards high-performance deep learning architecture and hardware accelerator design for robust analysis in diffuse correlation spectroscopy.

Computer methods and programs in biomedicine
This study proposes a compact deep learning (DL) architecture and a highly parallelized computing hardware platform to reconstruct the blood flow index (BFi) in diffuse correlation spectroscopy (DCS). We leveraged a rigorous analytical model to gener...

Highly valued subgoal generation for efficient goal-conditioned reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Goal-conditioned reinforcement learning is widely used in robot control, manipulating the robot to accomplish specific tasks by maximizing accumulated rewards. However, the useful reward signal is only received when the desired goal is reached, leadi...

CNN-Informer: A hybrid deep learning model for seizure detection on long-term EEG.

Neural networks : the official journal of the International Neural Network Society
Timely detecting epileptic seizures can significantly reduce accidental injuries of epilepsy patients and offer a novel intervention approach to improve their quality of life. Investigation on seizure detection based on deep learning models has achie...

Synchronization of time-delay dynamical networks via hybrid delayed impulses.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the synchronization problem of time-delay dynamical networks by means of hybrid delayed impulses, where synchronizing impulses and desynchronizing impulses can occur simultaneously. Some sufficient synchronization conditions a...

Roller compaction: Measuring ribbon porosity by terahertz spectroscopy and machine learning.

International journal of pharmaceutics
Roller compaction is a crucial unit operation in pharmaceutical manufacturing, with its ribbon porosity widely recognised as a critical quality attribute. Terahertz spectroscopy has emerged as a fast and non-destructive technique to measure porosity ...

CK-ATTnet: Medical image segmentation network based on convolutional kernel attention.

Computers in biology and medicine
The medical image partition model has a wide range of application prospects in medical diagnosis and treatment and has become an important auxiliary method to improve the diagnostic level by medical imaging analysis. After the feature extraction abil...

Predicting ergonomic risk among laboratory technicians using a Cheetah Optimizer-Integrated Deep Convolutional Neural Network.

Computers in biology and medicine
Medical laboratory technicians play a significant role in clinical units by conducting diagnostic tests and analyses. However, their job nature involving repetitive motions, prolonged standing or sitting, etc., leads to potential ergonomic risks. Thi...

LTMSegnet: Lightweight multi-scale medical image segmentation combining Transformer and MLP.

Computers in biology and medicine
Medical image segmentation is currently of a priori guiding significance in medical research and clinical diagnosis. In recent years, neural network-based methods have improved in terms of segmentation accuracy and become the mainstream in the field ...