Search
Search Results
-
Click-through rate prediction based on feature interaction and behavioral sequence
Click-through rate prediction is one of the hot topics in the recommendation and advertising systems field. The existing click-through rate...
-
Remote assessment of Parkinson’s disease symptom severity based on group interaction feature assistance
Telemonitoring is an effective way to assess the severity of Parkinson's disease (PD). Due to heterogeneity and small sample sizes, the multi-task...
-
Dynamic feature selection combining standard deviation and interaction information
Feature selection achieves dimensionality reduction by selecting some effective features from the original feature set. However, in the process of...
-
Interaction-based clustering algorithm for feature selection: a multivariate filter approach
In pattern recognition and data mining, feature selection is a preprocessing step during which the dimensions of data are reduced by removing...
-
CFDIL: a context-aware feature deep interaction learning for app recommendation
The rapid development of mobile Internet has spawned various mobile applications (apps). A large number of apps make it difficult for users to choose...
-
Action Recognition Model Based on Feature Interaction
In order to solve incomplete information expression and large amount of calculation, this paper proposes an action recognition model based on feature...
-
Analysis and Evaluation of Feature Selection and Feature Extraction Methods
Hand gestures are widely used in human-to-human and human-to-machine communication. Therefore, hand gesture recognition is a topic of great interest....
-
Sequence-based prediction of protein–protein interaction using auto-feature engineering of RNN-based model
PurposeThe intricate language of eukaryotic gene articulation remains deficiently comprehended. Notwithstanding the significance recommended by...
-
Multi-level Feature Enhancement and Interaction Network for Remote Sensing Image Semantic Segmentation
Exploring and exploiting discriminative multi-level information is crucial for Convolutional Neural Networks (CNNs) based remote sensing image...
-
Combining transformer global and local feature extraction for object detection
Convolutional neural network (CNN)-based object detectors perform excellently but lack global feature extraction and cannot establish global...
-
Person Re-Identification Based on Spatial Feature Learning and Multi-Granularity Feature Fusion
In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative...
-
An ensemble-based drug–target interaction prediction approach using multiple feature information with data balancing
BackgroundRecently, drug repositioning has received considerable attention for its advantage to pharmaceutical industries in drug development....
-
Manufacturing feature recognition method based on graph and minimum non-intersection feature volume suppression
Automatic manufacturing feature recognition (AFR) is a critical technology for realizing CAD/CAPP/CAM integration in the era of intelligent...
-
Discriminative multi-scale adjacent feature for person re-identification
Recently, discriminative and robust identification information has played an increasingly critical role in Person Re-identification (Re-ID). It is a...
-
Multimodal fake news detection through intra-modality feature aggregation and inter-modality semantic fusion
The prevalence of online misinformation, termed “fake news”, has exponentially escalated in recent years. These deceptive information, often rich...
-
Feature-Aware Network Based on Upper Triangular Interaction for Single Shot Detector
Dong, **ang Li, Feng Bai, Huihui Zhao, YaoConsidering the impact of the balance between real-time performance and detection accuracy, single-stage...
-
TFEN: two-stage feature enhancement network for single-image super-resolution
In recent years, deep convolution neural networks have made significant progress in single-image super-resolution (SISR). However, high-resolution...
-
Multi-Scene Smoke Detection Based on Multi-Feature Extraction Method
This study proposes a multi-scene smoke detection algorithm based on a multi-feature extraction method to address the problems of varying smoke...
-
TFITrack: Transformer Feature Integration Network for Object Tracking
Due to the ignoring of rich spatio-temporal and global contextual information with convolutional neural networks in features extraction, the...
-
Exploiting multi-scale hierarchical feature representation for visual tracking
Convolutional neural networks (CNNs) have been the dominant architectures for feature extraction tasks, but CNNs do not look for and focus on some...
