AIMC Topic: Neural Networks, Computer

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Boundary-aware context neural network for medical image segmentation.

Medical image analysis
Medical image segmentation can provide a reliable basis for further clinical analysis and disease diagnosis. With the development of convolutional neural networks (CNNs), medical image segmentation performance has advanced significantly. However, mos...

With or without human interference for precise age estimation based on machine learning?

International journal of legal medicine
Age estimation can aid in forensic medicine applications, diagnosis, and treatment planning for orthodontics and pediatrics. Existing dental age estimation methods rely heavily on specialized knowledge and are highly subjective, wasting time, and ene...

High-Frequency Ultrasound Dataset for Deep Learning-Based Image Quality Assessment.

Sensors (Basel, Switzerland)
This study aims at high-frequency ultrasound image quality assessment for computer-aided diagnosis of skin. In recent decades, high-frequency ultrasound imaging opened up new opportunities in dermatology, utilizing the most recent deep learning-based...

3DMesh-GAR: 3D Human Body Mesh-Based Method for Group Activity Recognition.

Sensors (Basel, Switzerland)
Group activity recognition is a prime research topic in video understanding and has many practical applications, such as crowd behavior monitoring, video surveillance, etc. To understand the multi-person/group action, the model should not only identi...

Deep Learning Capabilities for the Categorization of Microcalcification.

International journal of environmental research and public health
Breast cancer is the most common cancer in women worldwide. It is the most frequently diagnosed cancer among women in 140 countries out of 184 reporting countries. Lesions of breast cancer are abnormal areas in the breast tissues. Various types of br...

Improving robustness of automatic cardiac function quantification from cine magnetic resonance imaging using synthetic image data.

Scientific reports
Although having been the subject of intense research over the years, cardiac function quantification from MRI is still not a fully automatic process in the clinical practice. This is partly due to the shortage of training data covering all relevant c...

A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models.

Scientific reports
This study aims to develop an assumption-free data-driven model to accurately forecast COVID-19 spread. Towards this end, we firstly employed Bayesian optimization to tune the Gaussian process regression (GPR) hyperparameters to develop an efficient ...

Antemortem detection of Parkinson's disease pathology in peripheral biopsies using artificial intelligence.

Acta neuropathologica communications
The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized th...

Research on Object Detection of PCB Assembly Scene Based on Effective Receptive Field Anchor Allocation.

Computational intelligence and neuroscience
Vision-based object detection of PCB (printed circuit board) assembly scenes is essential in accelerating the intelligent production of electronic products. In particular, it is necessary to improve the detection accuracy as much as possible to ensur...

TATL: Task agnostic transfer learning for skin attributes detection.

Medical image analysis
Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task. However, we argue that such approaches are suboptimal because medical datasets are largely different from I...