AIMC Topic: Algorithms

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Purely Attention Based Local Feature Integration for Video Classification.

IEEE transactions on pattern analysis and machine intelligence
Recently, substantial research effort has focused on how to apply CNNs or RNNs to better capture temporal patterns in videos, so as to improve the accuracy of video classification. In this paper, we investigate the potential of a purely attention bas...

Viewport-Based CNN: A Multi-Task Approach for Assessing 360° Video Quality.

IEEE transactions on pattern analysis and machine intelligence
For 360° video, the existing visual quality assessment (VQA) approaches are designed based on either the whole frames or the cropped patches, ignoring the fact that subjects can only access viewports. When watching 360° video, subjects select viewpor...

Adversarial Joint-Learning Recurrent Neural Network for Incomplete Time Series Classification.

IEEE transactions on pattern analysis and machine intelligence
Incomplete time series classification (ITSC) is an important issue in time series analysis since temporal data often has missing values in practical applications. However, integrating imputation (replacing missing data) and classification within a mo...

Heterogeneous Graph Attention Network for Unsupervised Multiple-Target Domain Adaptation.

IEEE transactions on pattern analysis and machine intelligence
Domain adaptation, which transfers the knowledge from label-rich source domain to unlabeled target domains, is a challenging task in machine learning. The prior domain adaptation methods focus on pairwise adaptation assumption with a single source an...

Intelligent Localization Sampling System Based on Deep Learning and Image Processing Technology.

Sensors (Basel, Switzerland)
In this paper, deep learning and image processing technologies are combined, and an automatic sampling robot is proposed that can completely replace the manual method in the three-dimensional space when used for the autonomous location of sampling po...

A Pruning Method for Deep Convolutional Network Based on Heat Map Generation Metrics.

Sensors (Basel, Switzerland)
With the development of deep learning, researchers design deep network structures in order to extract rich high-level semantic information. Nowadays, most popular algorithms are designed based on the complexity of visible image features. However, com...

Deep Learning Algorithm-Based MRI Image in the Diagnosis of Diabetic Macular Edema.

Contrast media & molecular imaging
This study investigates the value of magnetic resonance imaging (MRI) based on a deep learning algorithm in the diagnosis of diabetic macular edema (DME) patients. A total of 96 patients with DME were randomly divided into the experimental group (  =...

Identification of Type 2 Diabetes Based on a Ten-Gene Biomarker Prediction Model Constructed Using a Support Vector Machine Algorithm.

BioMed research international
BACKGROUND: Type 2 diabetes is a major health concern worldwide. The present study is aimed at discovering effective biomarkers for an efficient diagnosis of type 2 diabetes.

Financial Market Sentiment Prediction Technology and Application Based on Deep Learning Model.

Computational intelligence and neuroscience
In the real world, there are a variety of situations that require strategy control, that is reinforcement learning, as a method for studying the decision-making and behavioral strategies of intelligence. It has received a lot of research and empirica...

MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification.

NMR in biomedicine
Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employ...