Bio-Inspired Computing: Theories and Applications
15th International Conference, BIC-TA 2020, Qingdao, China, October 23-25, 2020, Revised Selected Papers
Page
%P
68 Result(s)
-
Chapter and Conference Paper
A Literature Analysis of the Application of Artificial Intelligence in Judicial Adjudication
The progress of technology has a profound impact on the transformation of social life while judicial activities are no exception. In recent years, artificial intelligence such as big data, blockchains has wide...
-
Article
EEMD-ConvLSTM: a model for short-term prediction of two-dimensional wind speed in the South China Sea
Accurate prediction of sea surface wind speed is crucial for marine activities such as marine search and rescue, marine ship**, and marine fishing. Because of the gustiness of sea surface winds, the wind spe...
-
Article
The using effect of fuzzy analytic hierarchy process in project engineering risk management
This work aims to explore the effectiveness of the fuzzy analytic hierarchy process (FAHP) in project engineering risk management and comprehensively investigate the application of genetic algorithm (GA) and n...
-
Article
A unified and costless approach for improving small and long-tail object detection in aerial images of traffic scenarios
Object detection is an important and challenging task for the utilization of arterial images. However, in traffic scenarios, small-sized and long-tail distributed object detections are still major challenges f...
-
Chapter and Conference Paper
UCLD-Net: Decoupling Network via Unsupervised Contrastive Learning for Image Dehazing
From traditional algorithms based on handcrafted prior to learning algorithms based on neural networks, the image dehazing technique has gone through great development. The handcrafted prior-based methods need...
-
Chapter and Conference Paper
SG-Net: Semantic Guided Network for Image Dehazing
From traditional handcrafted priors to learning-based neural networks, image dehazing technique has gone through great development. In this paper, we propose an end-to-end Semantic Guided Network (SG-Net (Code...
-
Chapter and Conference Paper
Overcoming Catastrophic Forgetting for Fine-Tuning Pre-trained GANs
The great transferability of DNNs has induced a popular paradigm of “pre-training & fine-tuning”, by which a data-scarce task can be performed much more easily. However, compared to the existing efforts made i...
-
Chapter and Conference Paper
Automatic Model Selection Algorithm Based on BYY Harmony Learning for Mixture of Gaussian Process Functional Regressions Models
For finite mixture models, determining the number of components is referred to as model selection. This paper puts forward an automatic model selection algorithm based on Bayesian Ying-Yang (BYY) harmony learn...
-
Article
KG-DTI: a knowledge graph based deep learning method for drug-target interaction predictions and Alzheimer’s disease drug repositions
Drug repositioning, which recommends approved drugs to potential targets by predicting drug-target interactions (DTIs), can save the cost and shorten the period of drug development. In this work, we propose a ...
-
Chapter and Conference Paper
Augmented Feature Representation with Parallel Convolution for Cross-domain Facial Expression Recognition
Facial expression recognition (FER) has made significant progress in the past decade, but the inconsistency of distribution between different datasets greatly limits the generalization performance of a learned...
-
Article
Filippov FitzHugh-Nagumo Neuron Model with Membrane Potential Threshold Control Policy
In this paper, a novel FitzHugh-Nagumo (FHN) neuron model with membrane potential threshold control policy is proposed. As the membrane potential threshold control policy is a switching control policy, our pro...
-
Article
Event-Based Projective Synchronization for Different Dimensional Complex Dynamical Networks with Unknown Dynamics by Using Data-Driven Scheme
In this paper, the projective synchronization problem for different dimensional complex networks (CNs) with unknown dynamics is investigated. First, by selecting a projective matrix, the error system is obtain...
-
Article
Spatiotemporal dynamic of a coupled neutral-type neural network with time delay and diffusion
In this paper, a delayed neutral-type neural network with diffusion is considered. Three spatiotemporal dynamic problems of such network, i.e., stability, Turing instability and oscillation, are addressed in d...
-
Article
Adaptive control of manipulator based on neural network
With the development of economic science and technology, the development of computer vision has undergone rapid changes, and various products relying on computer vision are also more and more, such as smart ho...
-
Book and Conference Proceedings
-
Chapter and Conference Paper
NSF-Based Mixture of Gaussian Processes and Its Variational EM Algorithm
Mixture of Gaussian processes (MGP) is a powerful model for dealing with data with multi-modality. However, input distributions of Gaussian process (GP) components of an MGP are designed to be Gaussians, which...
-
Chapter and Conference Paper
Fully Test-Time Adaptation for Image Segmentation
When adopting a model from the source domain to the target domain, its performance usually degrades due to the domain shift problem. In clinical practice, the source data usually cannot be accessed during adap...
-
Chapter and Conference Paper
A Pointer-Generator Based Abstractive Summarization Model with Knowledge Distillation
The use of large-scale pre-trained models for text summarization has attracted increasing attention in the computer science community. However, pre-training models with millions of parameters and long training...
-
Chapter and Conference Paper
Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network
Brain atlases are of fundamental importance for analyzing the dynamic neurodevelopment in fetal brain studies. Since the brain size, shape, and anatomical structures change rapidly during the prenatal period, ...
-
Chapter and Conference Paper
STDA-inf: Style Transfer for Data Augmentation Through In-data Training and Fusion Inference
Style transfer has been effectively applied to data augmentation. However, previous work requires careful selection of style images out of the concerned datasets, and neglects the impact of style transfer on t...
