AIMC Topic: Neural Networks, Computer

Clear Filters Showing 11051 to 11060 of 31376 articles

Breaking Neural Reasoning Architectures With Metamorphic Relation-Based Adversarial Examples.

IEEE transactions on neural networks and learning systems
The ability to read, reason, and infer lies at the heart of neural reasoning architectures. After all, the ability to perform logical reasoning over language remains a coveted goal of Artificial Intelligence. To this end, models such as the Turing-co...

FAPNET: Feature Fusion with Adaptive Patch for Flood-Water Detection and Monitoring.

Sensors (Basel, Switzerland)
In satellite remote sensing applications, waterbody segmentation plays an essential role in mapping and monitoring the dynamics of surface water. Satellite image segmentation-examining a relevant sensor data spectrum and identifying the regions of in...

AI-Generated Face Image Identification with Different Color Space Channel Combinations.

Sensors (Basel, Switzerland)
With the rapid development of the Internet and information technology (in particular, generative adversarial networks and deep learning), network data are exploding. Due to the misuse of technology and inadequate supervision, deep-network-generated f...

DOPNet: Achieving Accurate and Efficient Point Cloud Registration Based on Deep Learning and Multi-Level Features.

Sensors (Basel, Switzerland)
Point cloud registration aims to find a rigid spatial transformation to align two given point clouds; it is widely deployed in many areas of computer vision, such as target detection, 3D localization, and so on. In order to achieve the desired result...

Data augmentation with improved regularisation and sampling for imbalanced blood cell image classification.

Scientific reports
Due to progression in cell-cycle or duration of storage, classification of morphological changes in human blood cells is important for correct and effective clinical decisions. Automated classification systems help avoid subjective outcomes and are m...

Computational modeling of color perception with biologically plausible spiking neural networks.

PLoS computational biology
Biologically plausible computational modeling of visual perception has the potential to link high-level visual experiences to their underlying neurons' spiking dynamic. In this work, we propose a neuromorphic (brain-inspired) Spiking Neural Network (...

A CNN-transformer fusion network for COVID-19 CXR image classification.

PloS one
The global health crisis due to the fast spread of coronavirus disease (Covid-19) has caused great danger to all aspects of healthcare, economy, and other aspects. The highly infectious and insidious nature of the new coronavirus greatly increases th...

Alpha-SGANet: A multi-attention-scale feature pyramid network combined with lightweight network based on Alpha-IoU loss.

PloS one
The design of deep convolutional neural networks has resulted in significant advances and successes in the field of object detection. However, despite these achievements, the high computational and memory costs of such object detection networks on th...

Deep Learning-Based Detection of Epileptiform Discharges for Self-Limited Epilepsy With Centrotemporal Spikes.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Centrotemporal spike-waves (CTSWs) are typical interictal epileptiform discharges (IEDs) observed in centrotemporal regions in self-limited epilepsy with centrotemporal spikes (SLECTS). This study aims to develop a deep learning-based approach for au...

Stain-Independent Deep Learning-Based Analysis of Digital Kidney Histopathology.

The American journal of pathology
Convolutional neural network (CNN)-based image analysis applications in digital pathology (eg, tissue segmentation) require a large amount of annotated data and are mostly trained and applicable on a single stain. Here, a novel concept based on stain...