Convolutive blind source separation method based on tensor decomposition by Baoze MA, Tianqi ZHANG, Zeliang AN, Pan DENG

“…A convolutive blind source separation algorithm was proposed based on tensor decomposition framework, to address the estimation of mixed filter matrix and the permutation alignment of frequency bin simultaneously.Firstly, the tensor models at all frequency bins were constructed according to the estimated autocorrelation matrix of the observed signals.Secondly, the factor matrix corresponding to each frequency bin was calculated by tensor decomposition technique as the estimated mixed filter matrix for that bin.Finally, a global optimal permutation strategy with power ratio as the permutation alignment measure was adopted to eliminate the permutation ambiguity in all the frequency bins.Experimental results demonstrate that the proposed method achieves better separation performance than other existing algorithms when dealing with convolutive mixed speech under different simulation conditions.…”
Get full text

Improved Hierarchical Convolutional Features for Robust Visual Object Tracking by Jinping Sun

“…Thus, to improve the tracking performance and robustness, an improved hierarchical convolutional features model is proposed into a correlation filter framework for visual object tracking. …”
Get full text

Monocular VO Based on Deep Siamese Convolutional Neural Network by Hongjian Wang, Xicheng Ban, Fuguang Ding, Yao Xiao, Jiajia Zhou

“…In this paper, we propose a new framework of deep neural network, named Deep Siamese convolutional neural network (DSCNN), and design a DL-based monocular VO relying on DSCNN. …”
Get full text

Epileptic Seizure Prediction With Multi-View Convolutional Neural Networks by Chien-Liang Liu, Bin Xiao, Wen-Hoar Hsaio, Vincent S. Tseng

“…Subsequently, this work proposes a multi-view convolutional neural network framework to predict the occurrence of epilepsy seizures with the goal of acquiring a shared representation of time-domain and frequency-domain features. …”
Get full text

Learning Transferable Convolutional Proxy by SMI-Based Matching Technique by Wei Jin, Nan Jia

“…In our framework, we firstly represent both source and target domains to feature vectors by two convolutional neural networks and then construct a proxy for each target domain sample in the source domain space. …”
Get full text

Osteoarthritis Classification Using Hybrid Quantum Convolutional Neural Network by Devansh Tikariha, Abdul Moomin, D. Jeyamani, P. Rukmani

“…This work explores the integration of quantum computing within a classical Convolutional Neural Network (CNN) framework, leveraging a VGG16 model enhanced with a quantum Convolutional Neural Network (QCNN) for the classification of knee osteoarthritis (OA) severity. …”
Get full text

A novel hybrid convolutional and transformer network for lymphoma classification by Mohamed Yacin Sikkandar, Sankar Ganesh Sundaram, Muteb Nasser Almeshari, S. Sabarunisha Begum, E. Siva Sankari, Yousef A. Alduraywish, Waeal J. Obidallah, Fahad Mansour Alotaibi

“…This study proposes a hybrid deep learning framework—Hybrid Convolutional and Transformer Network for Lymphoma Classification (HCTN-LC)—designed to enhance the precision and interpretability of lymphoma subtype classification. …”
Get full text

Identifying T cell antigen at the atomic level with graph convolutional network by Jinhao Que, Guangfu Xue, Tao Wang, Xiyun Jin, Zuxiang Wang, Yideng Cai, Wenyi Yang, Meng Luo, Qian Ding, Jinwei Zhang, Yilin Wang, Yuexin Yang, Fenglan Pang, Yi Hui, Zheng Wei, Jun Xiong, Shouping Xu, Yi Lin, Haoxiu Sun, Pingping Wang, Zhaochun Xu, Qinghua Jiang

“…Here we propose deepAntigen, a graph convolutional network-based framework, to identify T cell antigens at the atomic level. deepAntigen achieves excellent performance both in the prediction of antigen-human leukocyte antigen (HLA) binding and antigen-T cell receptor (TCR) interactions, which can provide comprehensive guidance for identification of T cell antigens. …”
Get full text

Battery Life Evaluation Method Based on Temporal Convolution Network by SUN Yushu, AN Juan, HUANG Cunqiang, ZHANG Shunzhen, DANG Yanyang, PEI Wei, TANG Xisheng

“…ObjectiveTo improve the technical economy of battery system applications, a temporal convolutional network (TCN) is employed to evaluate battery life from two perspectives: State of health (SOH) and remaining useful life (RUL). …”
Get full text

AI-driven point cloud framework for predicting solder joint reliability using 3D FEA data by Mohd Zubair Akhtar, Maximilian Schmid, Gordon Elger

“…This framework integrates 3D Convolutional Neural Networks (CNNs) and PointNet architectures to automatically extract complex spatial features from 3D FEA data. …”
Get full text

COVID-19 Data Analytics Using Extended Convolutional Technique by Anand Kumar Gupta, Asadi Srinivasulu, Olutayo Oyeyemi Oyerinde, Giovanni Pau, C. V. Ravikumar

Get full text

AdaptiveSwin-CNN: Adaptive Swin-CNN Framework with Self-Attention Fusion for Robust Multi-Class Retinal Disease Diagnosis by Imran Qureshi

“…In this study, the author proposes a hybrid deep learning framework in the form of AdaptiveSwin-CNN that combines Swin Transformers and Convolutional Neural Networks (CNNs) for the classification of multi-class retinal diseases. …”
Get full text

Bio-inspired motion detection models for improved UAV and bird differentiation: a novel deep learning framework by Najiba Said Hamed Al-Zadjali, Sundaravadivazhagan Balasubaramanian, Charles Savarimuthu, Emanuel O. Rances

Get full text

Integrated deep learning framework for driver distraction detection and real-time road object recognition in advanced driver assistance systems by Rakesh Salakapuri, Naveen Kumar Navuri, Thrimurthulu Vobbilineni, G. Ravi, Karthik Karmakonda, K. Asish vardhan

Get full text

Efficient and Motion Correction-Free Myocardial Perfusion Segmentation in Small MRI Data Using Deep Transfer Learning From Cine Images: A Promising Framework for Clinical Implement... by German Garcia-Jara, Angel Jimenez-Molina, Esteban Reyes, Nicolas Tapia-Rivas, Cristobal Ramos-Gomez, Jose De Grazia, Matias Sepulveda

Subjects: “…myocardial segmentation framework…”
Get full text

An efficient patient’s response predicting system using multi-scale dilated ensemble network framework with optimization strategy by Nalini Manogaran, Nirupama Panabakam, Durai Selvaraj, Koteeswaran Seerangan, Firoz Khan, Shitharth Selvarajan

Get full text

Mine Microseismic Signal Denoising Based on a Deep Convolutional Autoencoder by Ting Hu, Bin Xu, Yongfa Wang, Jiayi Zhu, Jiang Zhou, Zhongyi Wan

“…Therefore, this study introduces a deep learning method to improve the mapping function and sparsity of signals in the time-frequency domain and constructs a denoising framework based on a deep convolutional autoencoder to address the denoising problem of mine microseismic signals. …”
Get full text

Fault Identification Model Using Convolutional Neural Networks with Transformer Architecture by Yongxin Fan, Yiming Dang, Yangming Guo

“…To address this, the present study proposes a novel hybrid deep learning framework that integrates Convolutional Neural Networks (CNN) for feature extraction with Transformer architecture for temporal modeling. …”
Get full text

Exudate Detection for Diabetic Retinopathy Using Pretrained Convolutional Neural Networks by Muhammad Mateen, Junhao Wen, Nasrullah Nasrullah, Song Sun, Shaukat Hayat

“…In this paper, pretrained convolutional neural network- (CNN-) based framework has been proposed for the detection of exudate. …”
Get full text

Joint Character-Level Convolutional and Generative Adversarial Networks for Text Classification by Tianshi Wang, Li Liu, Huaxiang Zhang, Long Zhang, Xiuxiu Chen

“…In the framework, we first quantify the texts by a character-level convolutional neural network and input the textual features into an adversarial network and a classifier, respectively. …”
Get full text