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PMFNet: A Progressive Multichannel Fusion Network for Multimodal Sentiment Analysis
The core of multimodal sentiment analysis is to find effective encoding and fusion methods to make accurate predictions. However, previous works...
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Functional Tomography of Complex Systems Using Spectral Analysis of Multichannel Measurement Data
AbstractA new method has been proposed for determining the structure of complex biological and physical systems from their electromagnetic fields....
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MAF-Net: multidimensional attention fusion network for multichannel speech separation
Recent studies have shown that multichannel narrow-band speech separation achieves remarkable performance, while most successful deep learning-based...
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Multichannel Multimodal Emotion Analysis of Cross-Modal Feedback Interactions Based on Knowledge Graph
Multimodal sentiment analysis is a downstream branch task of sentiment analysis with high attention at present. Previous work in multimodal sentiment...
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Efficient FPGA implementation for sound source separation using direction-informed multichannel non-negative matrix factorization
Sound source separation (SSS) is a fundamental problem in audio signal processing, aiming to recover individual audio sources from a given mixture. A...
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Efficient parallel kernel based on Cholesky decomposition to accelerate multichannel nonnegative matrix factorization
Multichannel source separation has been a popular topic, and recently proposed methods based on the local Gaussian model have provided promising...
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An adaptive multichannel DeepLabv3 + for semantic segmentation of aerial images using improved Beluga Whale Optimization Algorithm
Semantic segmentation of aerial images plays a pivotal role in extracting detailed information about land cover, infrastructure, and natural...
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Research on Link Prediction Algorithms Based on Multichannel Structure Modelling
Today's link prediction methods are based on the network structure using a single-channel approach for prediction, and there is a lack of link...
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Neonatal seizure detection using deep belief networks from multichannel EEG data
Seizures in neonates happen to be one of the most difficult emergency circumstances to deal with. They are the first signs of significant...
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Kernel smoothing classification of multiattribute data in the belief function framework: Application to multichannel image segmentation
Bayesian approaches turn out to be inefficient when decision making involves many uncertain, imprecise or unreliable sources of information. The same...
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Light field angular super resolution based on residual channel attention and classification up-sampling
Current light field angular super resolution algorithms generate coarse viewpoint images due to their low learning ability and equally upsample all...
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Optimization Driven Spike Deep Belief Neural Network classifier: a deep-learning based Multichannel Spike Sorting Neural Signal Processor (NSP) module for high-channel-count Brain Machine Interfaces (BMIs)
An Optimization Driven Spike Deep Belief Neural Networks is a type of neural network that is inspired by the functioning of the human brain. It is a...
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Multichannel environmental sound segmentation
This paper proposes a multichannel environmental sound segmentation method. Environmental sound segmentation is an integrated method to achieve sound...
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EEG emotion recognition using multichannel weighted multiscale permutation entropy
Electroencephalogram (EEG) signal is a time-varying and nonlinear spatial discrete signal, which has been widely used in the field of emotion...
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Multicore implementation of a multichannel parallel graphic equalizer
Numerous signal processing applications are emerging on mobile computing systems. These applications are subject to responsiveness constraints for...
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Sampling formulas for 2D quaternionic signals associated with various quaternion Fourier and linear canonical transforms
The main purpose of this paper is to study different types of sampling formulas of quaternionic functions, which are bandlimited under various...
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Efficient space learning based on kernel trick and dimension reduction technique for multichannel motor imagery EEG signals classification
Electroencephalogram (EEG) signals show the electrical activity of the brain, which are one of the inputs of the brain–computer interface (BCI). The...
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Multichannel speech separation using hybrid GOMF and enthalpy-based deep neural networks
Speech signal is commonly debased by room reverberation and included noises in genuine climates. This paper focuses on disengaging objective speech...
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Cross-Lingual Entity Alignment via Two-Hop Neighbour Sampling and Distinguishable Relation Embedding
The task of aligning Knowledge Graphs involves learning and identifying entity nodes within the source and target Knowledge Graphs that refer to the...
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Deep ensemble learning approach for lower limb movement recognition from multichannel sEMG signals
Walking is a complex task that requires consistent practice to master, and it involves the synchronisation between the lower limbs and the brain,...
