AIMC Topic: Algorithms

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Optimal selection of diagnostic method for diabetes mellitus using complex bipolar fuzzy dynamic data.

Scientific reports
Diabetes mellitus refers to a collection of metabolic disorders that affect the way carbohydrates are processed in the body. It is a prominent worldwide health issue. Precise and reliable decision-making methods are critical for identifying the most ...

GGSYOLOv5: Flame recognition method in complex scenes based on deep learning.

PloS one
The continuous development of the field of artificial intelligence, not only makes people's lives more convenient but also plays a role in the supervision and protection of people's lives and property safety. News of the fire is not uncommon, and fir...

Automated recognition and segmentation of lung cancer cytological images based on deep learning.

PloS one
Compared with histological examination of lung cancer, cytology is less invasive and provides better preservation of complete morphology and detail. However, traditional cytological diagnosis requires an experienced pathologist to evaluate all sectio...

Artificial intelligent based control strategy for reach and grasp of multi-objects using brain-controlled robotic arm system.

Network (Bristol, England)
Brain-controlled robotic arm systems are designed to provide a method of communication and control for individuals with limited mobility or communication abilities. These systems can be beneficial for people who have suffered from a spinal cord injur...

BCT-Net: semantic-guided breast cancer segmentation on BUS.

Medical & biological engineering & computing
Accurately and swiftly segmenting breast tumors is significant for cancer diagnosis and treatment. Ultrasound imaging stands as one of the widely employed methods in clinical practice. However, due to challenges such as low contrast, blurred boundari...

Graph convolution network-based eeg signal analysis: a review.

Medical & biological engineering & computing
With the advancement of artificial intelligence technology, more and more effective methods are being used to identify and classify Electroencephalography (EEG) signals to address challenges in healthcare and brain-computer interface fields. The appl...

Sample-efficient and occlusion-robust reinforcement learning for robotic manipulation via multimodal fusion dualization and representation normalization.

Neural networks : the official journal of the International Neural Network Society
Recent advances in visual reinforcement learning (visual RL), which learns from high-dimensional image observations, have narrowed the gap between state-based and image-based training. However, visual RL continues to face significant challenges in ro...

Conditional diffusion model for recommender systems.

Neural networks : the official journal of the International Neural Network Society
Recommender systems are used to filter personalized information for users, as it help avoid information overload. The diffusion model is an advanced deep generative model that has been used in recommender systems due to its effectiveness in reconstru...

Robust graph structure learning under heterophily.

Neural networks : the official journal of the International Neural Network Society
A graph is a fundamental mathematical structure in characterizing relations between different objects and has been widely used on various learning tasks. Most methods implicitly assume a given graph to be accurate and complete. However, real data is ...

U3UNet: An accurate and reliable segmentation model for forest fire monitoring based on UAV vision.

Neural networks : the official journal of the International Neural Network Society
Forest fires pose a serious threat to the global ecological environment, and the critical steps in reducing the impact of fires are fire warning and real-time monitoring. Traditional monitoring methods, like ground observation and satellite sensing, ...