IEEE transactions on neural networks and learning systems
Feb 1, 2019
We present the global deep video representation learning to video-based person reidentification (re-ID) that aggregates local 3-D features across the entire video extent. Existing methods typically extract frame-wise deep features from 2-D convolutio...
IEEE transactions on bio-medical engineering
Feb 1, 2019
OBJECTIVE: To develop an automated vessel wall segmentation method using convolutional neural networks to facilitate the quantification on magnetic resonance (MR) vessel wall images of patients with intracranial atherosclerotic disease (ICAD).
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2019
This paper presents a deep associative neural network (DANN) based on unsupervised representation learning for associative memory. In brain, the knowledge is learnt by associating different types of sensory data, such as image and voice. The associat...
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2019
In this paper, a new prediction and identification method based on adaptive echo state network (AESN) is proposed to identify a class of discrete-time dynamic nonlinear systems (DDNS). Firstly, according to the characteristics of input signals, the r...
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2019
In this paper, a new type of neural networks, quaternion-valued memristive neural networks (QVMNNs) is formulated. On the basis of the differential inclusion principle and the Lyapunov functional method, fixed-time synchronization problem is consider...
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2019
Gaussian Processes (GPs) models have been successfully applied to the problem of learning from sequential observations. In such context, the family of Recurrent Gaussian Processes (RGPs) have been recently introduced with a specifically designed stru...
Spiking neural P systems (SN P systems) are a class of distributed and parallel neural-like computing models, inspired from the way neurons communicate by means of spikes. In this paper, a new variant of the systems, called SN P systems with learning...
BACKGROUND: Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural networks. The adven...
Effort-aware just-in-time (JIT) defect prediction is to rank source code changes based on the likelihood of detects as well as the effort to inspect such changes. Accurate defect prediction algorithms help to find more defects with limited effort. To...
Preparative biochemistry & biotechnology
Feb 1, 2019
Artificial neural networking (ANN) seems to be a promising soft sensor for implementing current approaches of quality by design (QbD) and process analytical technologies (PAT) in the biopharmaceutical industry. In this study, we aimed to implement be...
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