AIMC Topic: Neural Networks, Computer

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Utility of a novel integrated deep convolutional neural network for the segmentation of hip joint from computed tomography images in the preoperative planning of total hip arthroplasty.

Journal of orthopaedic surgery and research
PURPOSE: Preoperative three-dimensional planning is important for total hip arthroplasty. To simulate the placement of joint implants on computed tomography (CT), pelvis and femur must be segmented. Accurate and rapid segmentation of the hip joint is...

Interpretation of convolutional neural networks reveals crucial sequence features involving in transcription during fiber development.

BMC bioinformatics
BACKGROUND: Upland cotton provides the most natural fiber in the world. During fiber development, the quality and yield of fiber were influenced by gene transcription. Revealing sequence features related to transcription has a profound impact on cott...

English Text Readability Measurement Based on Convolutional Neural Network: A Hybrid Network Model.

Computational intelligence and neuroscience
Text readability is very important in meeting people's information needs. With the explosive growth of modern information, the measurement demand of text readability is increasing. In view of the text structure of words, sentences, and texts, a hybri...

Human Resource Planning and Configuration Based on Machine Learning.

Computational intelligence and neuroscience
Human resources are the core resources of an enterprise, and the demand forecasting plays a vital role in the allocation and optimization of human resources. Starting from the basic concepts of human resource forecasting, this paper employs the backp...

A Boosting-Based Deep Distance Metric Learning Method.

Computational intelligence and neuroscience
By leveraging neural networks, deep distance metric learning has yielded impressive results in computer vision applications. However, the existing approaches mostly focus a single deep distance metric based on pairs or triplets of samples. It is diff...

Video Analysis and System Construction of Basketball Game by Lightweight Deep Learning under the Internet of Things.

Computational intelligence and neuroscience
With the explosive growth of sports video data on the internet platform, how to scientifically manage this information has become a major challenge in the current big data era. In this context, a new lightweight player segmentation algorithm is propo...

Motion Fatigue State Detection Based on Neural Networks.

Computational intelligence and neuroscience
Aiming at the problem of fatigue state detection at the back of sports, a cascade deep learning detection system structure is designed, and a convolutional neural network fatigue state detection model based on multiscale pooling is proposed. Firstly,...

BC-DUnet-based segmentation of fine cracks in bridges under a complex background.

PloS one
Crack is the external expression form of potential safety risks in bridge construction. Currently, automatic detection and segmentation of bridge cracks remains the top priority of civil engineers. With the development of image segmentation technique...

Image Inpainting With Local and Global Refinement.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Image inpainting has made remarkable progress with recent advances in deep learning. Popular networks mainly follow an encoder-decoder architecture (sometimes with skip connections) and possess sufficiently large receptive field, i.e., larger than th...

Single Image Super-Resolution Quality Assessment: A Real-World Dataset, Subjective Studies, and an Objective Metric.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Numerous single image super-resolution (SISR) algorithms have been proposed during the past years to reconstruct a high-resolution (HR) image from its low-resolution (LR) observation. However, how to fairly compare the performance of different SISR a...