Computational intelligence and neuroscience
Jun 6, 2022
Deep learning is a branch of machine learning that uses neural networks to mimic the behaviour of the human brain. Various types of models are used in deep learning technology. This article will look at two important models and especially concentrate...
Computational intelligence and neuroscience
Jun 6, 2022
Multimodal tasks based on attention mechanism and language face numerous problems. Based on multimodal hierarchical attention mechanism and genetic neural network, this paper studies the application of image segmentation algorithm in data completion ...
Appetite
Jun 5, 2022
Design of experiments (DOE) is a family of statistical tools commonly used in food science to optimise recipes and facilitate new food development. In a novel cross-disciplinary twist, we propose to adapt DOE approach to the optimisation of restauran...
Analytical and bioanalytical chemistry
Jun 4, 2022
Since preparative chromatography is a sustainability challenge due to large amounts of consumables used in downstream processing of biomolecules, protein crystallization offers a promising alternative as a purification method. While the limited cryst...
Neural networks : the official journal of the International Neural Network Society
Jun 3, 2022
In many machine learning applications, data are coming with multiple graphs, which is known as the multiple graph learning problem. The problem of multiple graph learning is to learn consistent representation by exploiting the complementary informati...
Journal of computational chemistry
Jun 3, 2022
Machine learning methods have helped to advance wide range of scientific and technological field in recent years, including computational chemistry. As the chemical systems could become complex with high dimension, feature selection could be critical...
IEEE transactions on pattern analysis and machine intelligence
Jun 3, 2022
A sum-product network (SPN) is a probabilistic model, based on a rooted acyclic directed graph, in which terminal nodes represent probability distributions and non-terminal nodes represent convex sums (weighted averages) and products of probability d...
IEEE transactions on pattern analysis and machine intelligence
Jun 3, 2022
In neural networks, developing regularization algorithms to settle overfitting is one of the major study areas. We propose a new approach for the regularization of neural networks by the local Rademacher complexity called LocalDrop. A new regularizat...
IEEE transactions on pattern analysis and machine intelligence
Jun 3, 2022
Domain Adaptation aims at adapting the knowledge learned from a domain (source-domain) to another (target-domain). Existing approaches typically require a portion of task-relevant target-domain data a priori. We propose an approach, zero-shot deep do...
IEEE transactions on pattern analysis and machine intelligence
Jun 3, 2022
Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among others, ...