Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…By comparing the performance of different methods, this paper aims to provide references for researchers in the realm of image classification, promoting further development in this area.…”
Get full text

ECG Signal Classification Using MODWT and CNN for Early Detection of Cardiac Abnormalities by Mohammad Yusuf Hamadani, Zainul Abidin, Muhammad Fauzan Edy Purnomo

“…This study proposes a method that integrates Maximal Overlap Discrete Wavelet Transform (MODWT) for feature extraction with a Convolutional Neural Network (CNN) to enhance classification performance. …”
Get full text

Design and realization of compressor data abnormality safety monitoring and inducement traceability expert system. by Yuan Wang, Shaolin Hu

“…Additionally, it presents an intelligent system design method for fault tracing in compressors and localization of faults from different sources. This method starts from petrochemical big data and consists of three parts: fault dynamic knowledge graph construction, instrument data sliding fault-tolerant filtering, and the fusion and reasoning of fault dynamic knowledge graph and instrument data variation monitoring. …”
Get full text

A Comprehensive Investigation of Fraud Detection Behavior in Federated Learning by Sun Rui

“…This research delves into the application of Federated Learning (FL) models for detecting fraud across different financial bodies. FL facilitates decentralized training of models using local data, ensuring privacy, crucial for handling sensitive financial data. …”
Get full text

Feature Selection-Based Hierarchical Deep Network for Image Classification by Guiqing He, Jiaqi Ji, Haixi Zhang, Yuelei Xu, Jianping Fan

“…In this paper, a novel hierarchical deep network is proposed to combine the deep convolutional neural network and the feature selection-based tree classifier efficiently for image classification. …”
Get full text

Quality-Aware PPG-Based Blood Pressure Classification for Energy-Efficient Trustworthy BP Monitoring Devices With Reduced False Alarms by Yalagala Sivanjaneyulu, M. Sabarimalai Manikandan, Srinivas Boppu, Linga Reddy Cenkeramaddi

“…In this paper, we present four SQA methods and nine machine learning (ML) based BP classification models, including logistic regression, decision tree, random forest, multilayer perceptron, k-nearest neighbours, XGBoost, AdaBoost, Bagged Tree, and one-dimensional convolutional neural network (1D-CNN). Four SQA methods are based on the average magnitude difference function (AMDF/(SQA-M1)) features and the AMDF features with the total number of zero-crossings present in raw/original (SQA-M2), derivative (SQA-M3), and smoothed derivative (SQA-M4) PPG segment features. …”
Get full text

NDVI Estimation Throughout the Whole Growth Period of Multi-Crops Using RGB Images and Deep Learning by Jianliang Wang, Chen Chen, Jiacheng Wang, Zhaosheng Yao, Ying Wang, Yuanyuan Zhao, Yi Sun, Fei Wu, Dongwei Han, Guanshuo Yang, Xinyu Liu, Chengming Sun, Tao Liu

“…The Normalized Difference Vegetation Index (NDVI) is an important remote sensing index that is widely used to assess vegetation coverage, monitor crop growth, and predict yields. …”
Get full text

Multimodal sleep staging network based on obstructive sleep apnea by Jingxin Fan, Jingxin Fan, Jingxin Fan, Mingfu Zhao, Li Huang, Li Huang, Bin Tang, Bin Tang, Lurui Wang, Zhong He, Zhong He, Xiaoling Peng

“…Finally, multiple channel data are integrated to address the heterogeneity between different modalities effectively and alleviate the impact of OSA on sleep stages.ResultsWe evaluated MSDC-SSNet on three public datasets and our collection of PSG records of 17 OSA patients. …”
Get full text

Multi-modal emotional analysis in customer relation management and enhancing communication through integrated affective computing by W. Gracy Theresa, C. Pabitha, K. Revathi, Pornpimol Chawengsaksopark, Mithilesh Sathyanarayanan

“…This research delves into the possible uses of multi-modal emotional analysis across different businesses dealing with customers and builds a strong foundation.…”
Get full text

Classification of Buried Objects From Ground Penetrating Radar Images by Using Second-Order Deep Learning Models by Douba Jafuno, Ammar Mian, Guillaume Ginolhac, Nickolas Stelzenmuller

“…We also illustrate the interest of our models when training data and test sets are obtained from different weather modes or considerations.…”
Get full text

Advancing arabic dialect detection with hybrid stacked transformer models by Hager Saleh, Hager Saleh, Hager Saleh, Abdulaziz AlMohimeed, Rasha Hassan, Mandour M. Ibrahim, Saeed Hamood Alsamhi, Moatamad Refaat Hassan, Sherif Mostafa

“…The stacking model compares various models, including long-short-term memory (LSTM), gated recurrent units (GRU), convolutional neural network (CNN), and two transformer models using different word embedding. …”
Get full text

Blind source separation and unmanned aerial vehicle classification using CNN with hybrid cross-channel and spatial attention module by Jiangong Ni, Zhigang Zhou

“…In order to accurately and effectively identify different types of UAVs, a UAV category recognition method based on improved convolutional neural network (CNN) is proposed. …”
Get full text

Performance evaluation of enhanced deep learning classifiers for person identification and gender classification by Vasu Krishna Suravarapu, Hemprasad Yashwant Patil

“…The efficacy of the model is assessed concerning different outcome indicators. It is also compared with the recent competitive models. …”
Get full text

Buried penis; what buried the penis? by Mohamed Fawzy, Ahmed T. Hadidi

“…Patients were divided into 3 groups; group A: 13 patients with BP, group B: 14 patients with different grades of distal Hypospadias, and group C with 13 patients who were referred for circumcision (control group). …”
Get full text

Integrated deep network model with multi-head twofold attention for drug–target interaction prediction by Angelin Jeba P, Tamilpavai G

“…The MHTA mechanism enhances the model’s ability to focus on different aspects of drug and target features independently, effectively capturing intricate interaction patterns. …”
Get full text

Ensemble learning-based abnormality diagnosis in wrist skeleton radiographs using densenet variants voting by Sajid Khan, Faiqa Arshad, Maryam Zulfiqar, Muhammad Asif Khan, Sufyan Ali Memon

“…They used capsule network, 169-layer convolutional neural network, and group normalized convolutional neural network. …”
Get full text

Using Deep Learning to Predict Complex Systems: A Case Study in Wind Farm Generation by J. M. Torres, R. M. Aguilar

“…In this paper we propose using different deep-learning techniques and architectures to solve the problem of predicting wind generation in order to participate in the daily market, by making predictions 12 and 36 hours in advance. …”
Get full text

Skin Lesion Image Segmentation Algorithm Based on MC-UNet by Guihua Yang, Bingxing Pan

“…Aiming at the situation of dermatoscopic images with fuzzy lesion boundaries, variable morphology and high similarity to background, this paper proposes a skin lesion segmentation algorithm that achieves higher segmentation accuracy by combining existing convolutional neural network methods. The algorithm begins by using a Multiscale Residual Block (MRB) with different-sized convolutional kernels to enlarge the receptive field and extract multi-scale features of dermatoscopic images. …”
Get full text

A Configurable Accelerator for CNN-Based Remote Sensing Object Detection on FPGAs by Yingzhao Shao, Jincheng Shang, Yunsong Li, Yueli Ding, Mingming Zhang, Ke Ren, Yang Liu

“…Convolutional neural networks (CNNs) have been widely used in satellite remote sensing. …”
Get full text

Optimisation of Residual Network Using Data Augmentation and Ensemble Deep Learning for Butterfly Image Classification by Diniati Ruaika, Shofwatul Uyun

“…The dataset contains 75 different butterfly species, 9.285 training images, 375 testing images, and 375 validation images. …”
Get full text