AIMC Topic: Neural Networks, Computer

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Surface and underwater human pose recognition based on temporal 3D point cloud deep learning.

Scientific reports
Airborne surface and underwater human pose recognition are crucial for various safety and surveillance applications, including the detection of individuals in distress or drowning situations. However, airborne optical cameras struggle to achieve simu...

Neural networks from biological to artificial and vice versa.

Bio Systems
In this paper, we examine how deep learning can be utilized to investigate neural health and the difficulties in interpreting neurological analyses within algorithmic models. The key contribution of this paper is the investigation of the impact of a ...

Concept Graph Neural Networks for Surgical Video Understanding.

IEEE transactions on medical imaging
Analysis of relations between objects and comprehension of abstract concepts in the surgical video is important in AI-augmented surgery. However, building models that integrate our knowledge and understanding of surgery remains a challenging endeavor...

One-Shot Weakly-Supervised Segmentation in 3D Medical Images.

IEEE transactions on medical imaging
Deep neural networks typically require accurate and a large number of annotations to achieve outstanding performance in medical image segmentation. One-shot and weakly-supervised learning are promising research directions that reduce labeling effort ...

Deep Generalized Learning Model for PET Image Reconstruction.

IEEE transactions on medical imaging
Low-count positron emission tomography (PET) imaging is challenging because of the ill-posedness of this inverse problem. Previous studies have demonstrated that deep learning (DL) holds promise for achieving improved low-count PET image quality. How...

Robust Vascular Segmentation for Raw Complex Images of Laser Speckle Contrast Based on Weakly Supervised Learning.

IEEE transactions on medical imaging
Laser speckle contrast imaging (LSCI) is widely used for in vivo real-time detection and analysis of local blood flow microcirculation due to its non-invasive ability and excellent spatial and temporal resolution. However, vascular segmentation of LS...

An emotion recognition method based on EWT-3D-CNN-BiLSTM-GRU-AT model.

Computers in biology and medicine
This has become a significant study area in recent years because of its use in brain-machine interaction (BMI). The robustness problem of emotion classification is one of the most basic approaches for improving the quality of emotion recognition syst...

Predicting opinion using deep learning: From burning to sustainable management of organic waste in Indian State of Punjab.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
In winter season, the burning of crop residues for ease of sowing the next crop, along with industrial emissions and vehicular pollution leads to settling of a thick layer of smog in northern part of India. Therefore, to understand the opinion of far...

A hybrid deep learning approach to improve real-time effluent quality prediction in wastewater treatment plant.

Water research
Wastewater treatment plant (WWTP) operation is usually intricate due to large variations in influent characteristics and nonlinear sewage treatment processes. Effective modeling of WWTP effluent water quality can provide valuable decision-making supp...

Full virtual patient generated by artificial intelligence-driven integrated segmentation of craniomaxillofacial structures from CBCT images.

Journal of dentistry
OBJECTIVES: To assess the performance, time-efficiency, and consistency of a convolutional neural network (CNN) based automated approach for integrated segmentation of craniomaxillofacial structures compared with semi-automated method for creating a ...