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Learning sparse and meaningful representations through embodiment.

Neural networks : the official journal of the International Neural Network Society
How do humans acquire a meaningful understanding of the world with little to no supervision or semantic labels provided by the environment? Here we investigate embodiment with a closed loop between action and perception as one key component in this p...

Modality independent adversarial network for generalized zero shot image classification.

Neural networks : the official journal of the International Neural Network Society
Zero Shot Learning (ZSL) aims to classify images of unseen target classes by transferring knowledge from source classes through semantic embeddings. The core of ZSL research is to embed both visual representation of object instance and semantic descr...

Joint Local and Global Information Learning With Single Apex Frame Detection for Micro-Expression Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Micro-expressions (MEs) are rapid and subtle facial movements that are difficult to detect and recognize. Most recent works have attempted to recognize MEs with spatial and temporal information from video clips. According to psychological studies, th...

Can We Ditch Feature Engineering? End-to-End Deep Learning for Affect Recognition from Physiological Sensor Data.

Sensors (Basel, Switzerland)
To further extend the applicability of wearable sensors in various domains such as mobile health systems and the automotive industry, new methods for accurately extracting subtle physiological information from these wearable sensors are required. How...

An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques.

Sensors (Basel, Switzerland)
In recent years the advances in Artificial Intelligence (AI) have been seen to play an important role in human well-being, in particular enabling novel forms of human-computer interaction for people with a disability. In this paper, we propose a sEMG...

ClsGAN: Selective Attribute Editing Model based on Classification Adversarial Network.

Neural networks : the official journal of the International Neural Network Society
Attribution editing has achieved remarkable progress in recent years owing to the encoder-decoder structure and generative adversarial network (GAN). However, it remains challenging to generate high-quality images with accurate attribute transformati...

Adversarial symmetric GANs: Bridging adversarial samples and adversarial networks.

Neural networks : the official journal of the International Neural Network Society
Generative adversarial networks have achieved remarkable performance on various tasks but suffer from training instability. Despite many training strategies proposed to improve training stability, this issue remains as a challenge. In this paper, we ...

Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiase...

Guided Attention Inference Network.

IEEE transactions on pattern analysis and machine intelligence
With only coarse labels, weakly supervised learning typically uses top-down attention maps generated by back-propagating gradients as priors for tasks such as object localization and semantic segmentation. While these attention maps are intuitive and...

Sensor Fusion of Motion-Based Sign Language Interpretation with Deep Learning.

Sensors (Basel, Switzerland)
Sign language was designed to allow hearing-impaired people to interact with others. Nonetheless, knowledge of sign language is uncommon in society, which leads to a communication barrier with the hearing-impaired community. Many studies of sign lang...