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. …”
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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.…”
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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. …”
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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. …”
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Attention-mechanism-based tracking method for intelligent Internet of vehicles by Xu Kang, Bin Song, Jie Guo, Xiaojiang Du, Mohsen Guizani

“…Beyond the traditional Global Positioning System sensor, the image sensor can capture different kinds of vehicles, analyze their driving situation, and can interact with them. …”
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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. …”
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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. …”
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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. …”
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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. …”
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Academic Emotion Classification Using FER: A Systematic Review by Jeniffer Xin-Ying Lek, Jason Teo

“…Based on the search criteria, 701 publications were initially retrieved from five different digital databases, of which 48 studies have been chosen as primary studies for further analysis. …”
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An Efficient CNN for Hand X-Ray Overall Scoring of Rheumatoid Arthritis by Zijian Wang, Jian Liu, Zongyun Gu, Chuanfu Li

“…There was no statistical difference between the average scores given by two experienced radiologists and predicted scores from our model.…”
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Automation and Optimization of Food Process Using CNN and Six-Axis Robotic Arm by Youngjin Kim, Sangoh Kim

“…A comparative analysis between the Preliminary Coffee Sample (PCS) and Validation Coffee Sample (VCS) revealed that increasing roast intensity resulted in consistent trends for both samples, including an increase in weight loss and Gas sensor Initial Difference (GID) and a decrease in Sum of Pixel Grayscale Values (SPGVs). …”
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Connected and automated vehicle control at unsignalized intersection based on deep reinforcement learning in vehicle-to-infrastructure environment by Juan Chen, Vijayan Sugumaran, Peiyan Qu

“…The proposed method is validated in a simulation environment with different traffic flow and market penetration under the mixed traffic conditions of automated vehicles and human-driving vehicles. …”
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Deep learning on medical image analysis by Jiaji Wang, Shuihua Wang, Yudong Zhang

“…The paper covers the structure of CNN and its advances and explores the different types of transfer learning strategies as well as classic pre‐trained models. …”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…Following model fusion, the AUC improved to 0.783 (95% CI: 0.724–0.841). The difference in performance between the fusion model and the traditional machine learning model was statistically significant (p = 0.036). …”
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Racism Detection by Analyzing Differential Opinions Through Sentiment Analysis of Tweets Using Stacked Ensemble GCR-NN Model by Ernesto Lee, Furqan Rustam, Patrick Bernard Washington, Fatima El Barakaz, Wajdi Aljedaani, Imran Ashraf

“…Social media opinions and remarks provocating racial differences have been regarded as a serious threat to social, political, and cultural stability and have threatened the peace of different countries. …”
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Research on unsupervised domain adaptive bearing fault diagnosis method by WU ShengKai, SHAO Xing, WANG CuiXiang, GAO Jun

“…Aiming at the problem that the bearing fault diagnosis algorithm based on deep learning has poor diagnosis performance when the fault samples are lack of labels in different working conditions and real environmentsly, an unsupervised domain adaptive bearing fault diagnosis method was proposed to realize the unsupervised fault diagnosis of bearings under different working conditions. …”
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Efficient Implementation of Matrix-Based Image Processing Algorithms for IoT Applications by Sorin Zoican, Roxana Zoican

“…The proposed method uses CNN in a different way, not for artificial intelligence algorithms, but for matrix calculations using CNN resources effectively while maintaining the accuracy of the calculations. …”
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Fault Diagnosis Method for Main Pump Motor Shielding Sleeve Based on Attention Mechanism and Multi-Source Data Fusion by Nengqing Liu, Xuewei Xiang, Hui Li, Zhi Chen, Peng Jiang

“…Then, on the basis of the AM-MSCNN, a convolutional neural network structure based on the attention mechanism for multi-scale and multi-source data fusion (AM-MSMDF-CNN) is proposed to further fuse the primary fusion features of different channels of torque, rotational speed, voltage, and current. …”
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Towards the Development of the Clinical Decision Support System for the Identification of Respiration Diseases via Lung Sound Classification Using 1D-CNN by Syed Waqad Ali, Muhammad Munaf Rashid, Muhammad Uzair Yousuf, Sarmad Shams, Muhammad Asif, Muhammad Rehan, Ikram Din Ujjan

“…This study presents a Clinical Decision Support System (CDSS) for the early detection of respiratory disorders using a one-dimensional convolutional neural network (1D-CNN) model. The ICBHI 2017 Breathing Sound Database, which contains samples of different breathing sounds, was used in this research. …”
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