AIMC Topic: Neural Networks, Computer

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Using deep neural networks to disentangle visual and semantic information in human perception and memory.

Nature human behaviour
Mental representations of familiar categories are composed of visual and semantic information. Disentangling the contributions of visual and semantic information in humans is challenging because they are intermixed in mental representations. Deep neu...

Spatial relation categorization in infants and deep neural networks.

Cognition
Spatial relations, such as above, below, between, and containment, are important mediators in children's understanding of the world (Piaget, 1954). The development of these relational categories in infancy has been extensively studied (Quinn, 2003) y...

Multimodal Biomedical Image Segmentation using Multi-Dimensional U-Convolutional Neural Network.

BMC medical imaging
Deep learning recently achieved advancement in the segmentation of medical images. In this regard, U-Net is the most predominant deep neural network, and its architecture is the most prevalent in the medical imaging society. Experiments conducted on ...

Prediction of certainty in artificial intelligence-enabled electrocardiography.

Journal of electrocardiology
BACKGROUND: The 12‑lead ECG provides an excellent substrate for artificial intelligence (AI) enabled prediction of various cardiovascular diseases. However, a measure of prediction certainty is lacking.

Evaluation and screening of technology start-ups based on PCA and GA-BPNN.

PloS one
PURPOSE: Due to the existence of information opacity, there is a common problem of adverse selection in the process of screening alternative technology start-ups (TSs) and determining investment targets by venture capital institutions, which does not...

Residual current detection method based on improved VMD-BPNN.

PloS one
To further enhance the residual current detection capability of low-voltage distribution networks, an improved adaptive residual current detection method that combines variational modal decomposition (VMD) and BP neural network (BPNN) is proposed. Fi...

A lagrange programming neural network approach for nuclear norm optimization.

PloS one
This article proposes a continuous-time optimization approch instead of tranditional optimiztion methods to address the nuclear norm minimization (NNM) problem. Refomulating the NNM into a matrix form, we propose a Lagrangian programming neural netwo...

A novel fault diagnosis method for second-order bandpass filter circuit based on TQWT-CNN.

PloS one
To accurately locate faulty components in analog circuits, an analog circuit fault diagnosis method based on Tunable Q-factor Wavelet Transform(TQWT) and Convolutional Neural Network (CNN) is proposed in this paper. Firstly, the Grey Wolf algorithm (...

Machine learning/artificial intelligence in sports medicine: state of the art and future directions.

Journal of ISAKOS : joint disorders & orthopaedic sports medicine
Machine learning (ML) is changing the way health care is practiced and recent applications of these novel statistical techniques have started to impact orthopaedic sports medicine. Machine learning enables the analysis of large volumes of data to est...

Fast Real-Time Brain Tumor Detection Based on Stimulated Raman Histology and Self-Supervised Deep Learning Model.

Journal of imaging informatics in medicine
In intraoperative brain cancer procedures, real-time diagnosis is essential for ensuring safe and effective care. The prevailing workflow, which relies on histological staining with hematoxylin and eosin (H&E) for tissue processing, is resource-inten...