AIMC Topic: Neural Networks, Computer

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Crop Mapping Using the Historical Crop Data Layer and Deep Neural Networks: A Case Study in Jilin Province, China.

Sensors (Basel, Switzerland)
Machine learning combined with satellite image time series can quickly, and reliably be implemented to map crop distribution and growth monitoring necessary for food security. However, obtaining a large number of field survey samples for classifier t...

A deep learning approach to fight illicit trafficking of antiquities using artefact instance classification.

Scientific reports
We approach the task of detecting the illicit movement of cultural heritage from a machine learning perspective by presenting a framework for detecting a known artefact in a new and unseen image. To this end, we explore the machine learning problem o...

Artificial Intelligence-based Machine English-Assisted Translation in the Internet of Things Environment.

Computational intelligence and neuroscience
With the development of Internet of Things technology, the things that machines do instead of humans are becoming more and more complicated. Machine translation has developed rapidly in the past few decades, and the translation system has also been g...

AAF-Net: Scene text detection based on attention aggregation features.

PloS one
With the advent of the era of artificial intelligence, text detection is widely used in the real world. In text detection, due to the limitation of the receptive field of the neural network, most existing scene text detection methods cannot accuratel...

New deep learning method for efficient extraction of small water from remote sensing images.

PloS one
Extracting water bodies from remote sensing images is important in many fields, such as in water resources information acquisition and analysis. Conventional methods of water body extraction enhance the differences between water bodies and other inte...

Automated Lung Cancer Segmentation Using a PET and CT Dual-Modality Deep Learning Neural Network.

International journal of radiation oncology, biology, physics
PURPOSE: To develop an automated lung tumor segmentation method for radiation therapy planning based on deep learning and dual-modality positron emission tomography (PET) and computed tomography (CT) images.

Synergy of Spin-Orbit Torque and Built-In Field in Magnetic Tunnel Junctions with Tilted Magnetic Anisotropy: Toward Tunable and Reliable Spintronic Neurons.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Owing to programmable nonlinear dynamics, magnetic domain wall (DW)-based devices can be configured to function as spintronic neurons, promising to execute sophisticated tasks as a human brain. Developing energy-efficient, CMOS compatible, reliable, ...

DP Compress: A Model Compression Scheme for Generating Efficient Deep Potential Models.

Journal of chemical theory and computation
Machine-learning-based interatomic potential energy surface (PES) models are revolutionizing the field of molecular modeling. However, although much faster than electronic structure schemes, these models suffer from costly computations via deep neura...

Toward intraoperative tissue classification: exploiting signal feedback from an ultrasonic aspirator for brain tissue differentiation.

International journal of computer assisted radiology and surgery
PURPOSE: During brain tumor surgery, care must be taken to accurately differentiate between tumorous and healthy tissue, as inadvertent resection of functional brain areas can cause severe consequences. Since visual assessment can be difficult during...

Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction.

IEEE transactions on pattern analysis and machine intelligence
A lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of deep convolutional neural networks (DCNNs). In the recent works, the texture features either correspond to components of a l...