AIMC Topic: Neural Networks, Computer

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Deep Cognitive Gate: Resembling Human Cognition for Saliency Detection.

IEEE transactions on pattern analysis and machine intelligence
Saliency detection by human refers to the ability to identify pertinent information using our perceptive and cognitive capabilities. While human perception is attracted by visual stimuli, our cognitive capability is derived from the inspiration of co...

Hierarchical and Self-Attended Sequence Autoencoder.

IEEE transactions on pattern analysis and machine intelligence
It is important and challenging to infer stochastic latent semantics for natural language applications. The difficulty in stochastic sequential learning is caused by the posterior collapse in variational inference. The input sequence is disregarded i...

Deep Learning Adapted to Differential Neural Networks Used as Pattern Classification of Electrophysiological Signals.

IEEE transactions on pattern analysis and machine intelligence
This manuscript presents the design of a deep differential neural network (DDNN) for pattern classification. First, we proposed a DDNN topology with three layers, whose learning laws are derived from a Lyapunov analysis, justifying local asymptotic c...

Semi-Supervised Domain Adaptation for Multi-Label Classification on Nonintrusive Load Monitoring.

Sensors (Basel, Switzerland)
Nonintrusive load monitoring (NILM) is a technology that analyzes the load consumption and usage of an appliance from the total load. NILM is becoming increasingly important because residential and commercial power consumption account for about 60% o...

Hybrid SFNet Model for Bone Fracture Detection and Classification Using ML/DL.

Sensors (Basel, Switzerland)
An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consuming process. The development of machine learning (ML), as well as deep learning (DL), has set a new path in medical image diagnosis. In this study, we pro...

In-Field Automatic Identification of Pomegranates Using a Farmer Robot.

Sensors (Basel, Switzerland)
Ground vehicles equipped with vision-based perception systems can provide a rich source of information for precision agriculture tasks in orchards, including fruit detection and counting, phenotyping, plant growth and health monitoring. This paper pr...

DCSE:Double-Channel-Siamese-Ensemble model for protein protein interaction prediction.

BMC genomics
BACKGROUND: Protein-protein interaction (PPI) is very important for many biochemical processes. Therefore, accurate prediction of PPI can help us better understand the role of proteins in biochemical processes. Although there are many methods to pred...

Hyperspectral Image Classification Model Using Squeeze and Excitation Network with Deep Learning.

Computational intelligence and neuroscience
In the domain of remote sensing, the classification of hyperspectral image (HSI) has become a popular topic. In general, the complicated features of hyperspectral data cause the precise classification difficult for standard machine learning approache...

Coupled Attention Framework of Convolutional Neural Network Based on Computer Intelligence.

Computational intelligence and neuroscience
Using an attention mechanism based on the convolutional neural networks (CNNs) improves the performance of computer vision tasks by enhancing the representation of the features. The existing attention methods enhance the expression of the features by...

BrainNet: Optimal Deep Learning Feature Fusion for Brain Tumor Classification.

Computational intelligence and neuroscience
Early detection of brain tumors can save precious human life. This work presents a fully automated design to classify brain tumors. The proposed scheme employs optimal deep learning features for the classification of FLAIR, T1, T2, and T1CE tumors. I...