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A Deep Learning-Based Semantic Segmentation Model Using MCNN and Attention Layer for Human Activity Recognition.

Sensors (Basel, Switzerland)
With the development of wearable devices such as smartwatches, several studies have been conducted on the recognition of various human activities. Various types of data are used, e.g., acceleration data collected using an inertial measurement unit se...

Being ostensive (reply to commentaries on "Expression unleashed").

The Behavioral and brain sciences
One of our main goals with "Expression unleashed" was to highlight the distinctive, ostensive nature of human communication, and the many roles that ostension can play in human behavior and society. The commentaries we received forced us to be more p...

Power fingerprint identification based on the improved V-I trajectory with color encoding and transferred CBAM-ResNet.

PloS one
In power fingerprint identification, feature information is insufficient when using a single feature to identify equipment, and small load data of specific customers, difficult to meet the refined equipment classification needs. A power fingerprint i...

Human-Computer Interaction with a Real-Time Speech Emotion Recognition with Ensembling Techniques 1D Convolution Neural Network and Attention.

Sensors (Basel, Switzerland)
Emotions have a crucial function in the mental existence of humans. They are vital for identifying a person's behaviour and mental condition. Speech Emotion Recognition (SER) is extracting a speaker's emotional state from their speech signal. SER is ...

ResSKNet-SSDP: Effective and Light End-To-End Architecture for Speaker Recognition.

Sensors (Basel, Switzerland)
In speaker recognition tasks, convolutional neural network (CNN)-based approaches have shown significant success. Modeling the long-term contexts and efficiently aggregating the information are two challenges in speaker recognition, and they have a c...

Self-attention learning network for face super-resolution.

Neural networks : the official journal of the International Neural Network Society
Existing face super-resolution methods depend on deep convolutional networks (DCN) to recover high-quality reconstructed images. They either acquire information in a single space by designing complex models for direct reconstruction, or employ additi...

Ensemble deep learning enhanced with self-attention for predicting immunotherapeutic responses to cancers.

Frontiers in immunology
INTRODUCTION: Despite the many benefits immunotherapy has brought to patients with different cancers, its clinical applications and improvements are still hindered by drug resistance. Fostering a reliable approach to identifying sufferers who are sen...

Toward Region-Aware Attention Learning for Scene Graph Generation.

IEEE transactions on neural networks and learning systems
Scene graph generation (SGGen) is a challenging task due to a complex visual context of an image. Intuitively, the human visual system can volitionally focus on attended regions by salient stimuli associated with visual cues. For example, to infer th...