AIMC Topic: Neural Networks, Computer

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Learning lightweight super-resolution networks with weight pruning.

Neural networks : the official journal of the International Neural Network Society
Single image super-resolution (SISR) has achieved significant performance improvements due to the deep convolutional neural networks (CNN). However, the deep learning-based method is computationally intensive and memory demanding, which limit its pra...

Hebbian semi-supervised learning in a sample efficiency setting.

Neural networks : the official journal of the International Neural Network Society
We propose to address the issue of sample efficiency, in Deep Convolutional Neural Networks (DCNN), with a semi-supervised training strategy that combines Hebbian learning with gradient descent: all internal layers (both convolutional and fully conne...

A novel M-SegNet with global attention CNN architecture for automatic segmentation of brain MRI.

Computers in biology and medicine
In this paper, we propose a novel M-SegNet architecture with global attention for the segmentation of brain magnetic resonance imaging (MRI). The proposed architecture consists of a multiscale deep network at the encoder side, deep supervision at the...

Fast and Accurate Object Detection in Remote Sensing Images Based on Lightweight Deep Neural Network.

Sensors (Basel, Switzerland)
Deep learning-based object detection in remote sensing images is an important yet challenging task due to a series of difficulties, such as complex geometry scene, dense target quantity, and large variant in object distributions and scales. Moreover,...

An artifıcial ıntelligence approach to automatic tooth detection and numbering in panoramic radiographs.

BMC medical imaging
BACKGROUND: Panoramic radiography is an imaging method for displaying maxillary and mandibular teeth together with their supporting structures. Panoramic radiography is frequently used in dental imaging due to its relatively low radiation dose, short...

A deep learning method for single-trial EEG classification in RSVP task based on spatiotemporal features of ERPs.

Journal of neural engineering
. Single-trial electroencephalography (EEG) classification is of great importance in the rapid serial visual presentation (RSVP) task. Convolutional neural networks (CNNs), as one of the mainstream deep learning methods, have been proven to be effect...

Unveiling functions of the visual cortex using task-specific deep neural networks.

PLoS computational biology
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We r...

Advertising Click-Through Rate Prediction Based on CNN-LSTM Neural Network.

Computational intelligence and neuroscience
In the era of big data information, how to effectively predict and analyze the click-through rate of information advertising is the key for enterprises in various fields to seek returns. The point rate prediction of advertising is one of the core con...

Demystifying artificial intelligence and deep learning in dentistry.

Brazilian oral research
Artificial intelligence (AI) is a general term used to describe the development of computer systems which can perform tasks that normally require human cognition. Machine learning (ML) is one subfield of AI, where computers learn rules from data, cap...