AIMC Topic: Neural Networks, Computer

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Translating medical image to radiological report: Adaptive multilevel multi-attention approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Medical imaging techniques are widely employed in disease diagnosis and treatment. A readily available medical report can be a useful tool in assisting an expert for investigating the patient's health. A radiologist can bene...

Nonideality-Aware Training for Accurate and Robust Low-Power Memristive Neural Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever-increasing computing requirements of these structures have contributed to a desire for novel technologies and paradigms, includi...

Tooth detection for each tooth type by application of faster R-CNNs to divided analysis areas of dental panoramic X-ray images.

Radiological physics and technology
This study aimed to propose a computerized method for detecting the tooth region for each tooth type as the initial stage in the development of a computer-aided diagnosis (CAD) scheme for dental panoramic X-ray images. Our database consists of 160 pa...

Malignant Bone Tumors Diagnosis Using Magnetic Resonance Imaging Based on Deep Learning Algorithms.

Medicina (Kaunas, Lithuania)
: Malignant bone tumors represent a major problem due to their aggressiveness and low survival rate. One of the determining factors for improving vital and functional prognosis is the shortening of the time between the onset of symptoms and the momen...

Multilevel Structural Components Detection and Segmentation toward Computer Vision-Based Bridge Inspection.

Sensors (Basel, Switzerland)
Bridge inspection plays a critical role in mitigating the safety risks associated with bridge deterioration and decay. CV (computer vision) technology can facilitate bridge inspection by accurately automating the structural recognition tasks, especia...

Content Swapping: A New Image Synthesis for Construction Sign Detection in Autonomous Vehicles.

Sensors (Basel, Switzerland)
Construction signs alert drivers to the dangers of abnormally blocked roads. In the case of autonomous vehicles, construction signs should be detected automatically to prevent accidents. One might think that we can accomplish the goal easily using th...

CIM-Based Smart Pose Detection Sensors.

Sensors (Basel, Switzerland)
The majority of digital sensors rely on von Neumann architecture microprocessors to process sampled data. When the sampled data require complex computation for 24×7, the processing element will a consume significant amount of energy and computation r...

Fusing pre-trained convolutional neural networks features for multi-differentiated subtypes of liver cancer on histopathological images.

BMC medical informatics and decision making
Liver cancer is a malignant tumor with high morbidity and mortality, which has a tremendous negative impact on human survival. However, it is a challenging task to recognize tens of thousands of histopathological images of liver cancer by naked eye, ...

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials.

Nature communications
This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neural network approach for learning interatomic potentials from ab-initio calculations for molecular dynamics simulations. While most contemporary symmetry-aw...

Prediction and Diagnosis of Respiratory Disease by Combining Convolutional Neural Network and Bi-directional Long Short-Term Memory Methods.

Frontiers in public health
OBJECTIVE: Based on the respiratory disease big data platform in southern Xinjiang, we established a model that predicted and diagnosed chronic obstructive pulmonary disease, bronchiectasis, pulmonary embolism and pulmonary tuberculosis, and provided...