Search
Search Results
-
Essential genes identification model based on sequence feature map and graph convolutional neural network
BackgroundEssential genes encode functions that play a vital role in the life activities of organisms, encompassing growth, development, immune...
-
Essential Tremor
Essential tremor (ET) is a chronic, progressive neurologic disease. Its central feature is a 4–12-Hz kinetic tremor (i.e., tremor occurring during...
-
Portrait Matting Network with Essential Feature Mining and Fusion
We propose an end-to-end portrait matting algorithm that emphasizes the mining and fusion of critical features to achieve higher accuracy. Previous...
-
Feature ranking based consensus clustering for feature subset selection
Feature subset selection problem is an NP hard problem and there is a need for computationally efficient algorithms that find near optimal feature...
-
Essential Blepharospasm
Benign essential blepharospasm (BEB) is a focal facial dystonia characterised by involuntary forced eyelids closure due to periorbital and facial...
-
Multimodal emotion recognition model via hybrid model with improved feature level fusion on facial and EEG feature set
In recent years, academics have placed a high value on multi-modal emotion identification, as well as extensive research has been conducted in the...
-
Data stream classification in dynamic feature space using feature map**
Stream learning in dynamic feature space has evolved into an immensely popular field. This problem assumes that each instance of the data stream may...
-
Essential Tremor
Essential tremor (ET), recognized as the most common movement disorder, silently permeates through populations, often with patients oblivious to...
-
Investigation of machine learning algorithms on heart disease through dominant feature detection and feature selection
Heart diseases are an essential research topic in healthcare institutions around the world. Therefore, using machine learning and optimization...
-
Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning
Internet of Things (IoT) devices are widely used but also vulnerable to cyberattacks that can cause security issues. To protect against this, machine...
-
FE-YOLO: YOLO ship detection algorithm based on feature fusion and feature enhancement
The technology for detecting maritime targets is crucial for realizing ship intelligence. However, traditional detection algorithms are not ideal due...
-
Feature importance feedback with Deep Q process in ensemble-based metaheuristic feature selection algorithms
Feature selection is an indispensable aspect of modern machine learning, especially for high-dimensional datasets where overfitting and computational...
-
Determining the best feature combination through text and probabilistic feature analysis for GPT-2-based mobile app review detection
Mobile apps, used by many people worldwide, have become an essential part of life. Before using a mobile app, users judge the reliability of apps...
-
A robust feature matching algorithm based on adaptive feature fusion combined with image superresolution reconstruction
With the development of image feature matching technology, feature matching algorithms based on deep learning have achieved excellent results, but in...
-
Enhancing intrusion detection recursive feature elimination with resampling in WSN
With the proliferation of technologies such as the Internet of Things, Cloud computing, and Social Networking, large quantities of network traffic...
-
A Feature Selection Method Based on Feature-Label Correlation Information and Self-Adaptive MOPSO
Feature selection can be seen as a multi-objective task, where the goal is to select a subset of features that exhibit minimal correlation among...
-
Parkinson’s disease classification using nature inspired feature selection and recursive feature elimination
New progress in machine learning (ML) have paved the way for solving various existing complex problems, including in the medical field. In the...
-
FESSD:SSD target detection based on feature fusion and feature enhancement
In recent years, significant breakthroughs have been made in target detection. However, although the existing two-stage target detection algorithm...
-
Feature extraction and classification algorithm, which one is more essential? An experimental study on a specific task of vibration signal diagnosis
With the development of machine learning, a data-driven model has been widely used in vibration signal fault diagnosis. Most data-driven machine...
-
Resformer: Local Frame-Level Feature and Global Segment-Level Feature Joint Learning for Speaker Verification
In this paper, we propose a hybrid network structure to achieve more discriminant feature representations for speaker recognition, termed Resformer,...
