Human Skin Detection Using RGB, HSV and YCbCr Color Models

Statistical Color Models with Application to Skin Detection

Jones, M., & Rehg, J. M. (2002) · International Journal of Computer Vision · doi:10.1023/a:1013200319198 · Cited by 1,542

A Survey on Pixel-Based Skin Color Detection Techniques

Vezhnevets, V., Sazonov, V., & Andreeva, A. D. (2003) · Cited by 936

Statistical color models with application to skin detection

Jones, M., & Rehg, J. M. (2003) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.1999.786951 · Cited by 491

Comparative Study of Skin Color Detection and Segmentation in HSV and YCbCr Color Space

Shaik, K. B., Ganesan, P., Kalist, V., Sathish, B. S., & Jenitha, J. M. M. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.07.362 · Cited by 346

Comparison of five color models in skin pixel classification

Zarit, B. D., Super, B. J., & Quek, F. K. H. (2003) · Analysis and Modeling of Faces and Gestures · doi:10.1109/ratfg.1999.799224 · Cited by 333

A novel skin color model in YCbCr color space and its application to human face detection

Phung, S. L., Bouzerdoum, A., & Chai, D. (2003) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2002.1038016 · Cited by 261

A Bayesian approach to skin color classification in YCbCr color space

Chai, D., & Bouzerdoum, A. (2002) · doi:10.1109/tencon.2000.888774 · Cited by 251

A comparative assessment of three approaches to pixel-level human skin-detection

Brand, J., & Mason, J. S. (2002) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2000.905653 · Cited by 227

Optimum color spaces for skin detection

Albiol, A., Torres, L., & Delp, E. J. (2002) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2001.958968 · Cited by 195

A Fusion Approach for Efficient Human Skin Detection

Tan, W. R., Chan, C. S., Yogarajah, P., & Condell, J. V. (2011) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2011.2172451 · Cited by 165

A Review of Machine Learning and Deep Learning for Object Detection, Semantic Segmentation, and Human Action Recognition in Machine and Robotic Vision

Manakitsa, N., Maraslidis, G. S., Moysis, L., & Fragulis, G. F. (2024) · Technologies · doi:10.3390/technologies12020015 · Cited by 355

Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Dataset

Groh, M., Harris, C., Soenksen, L. R., Lau, F., Han, R., Kim, A., Koochek, A., & Badri, O. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00201 · Cited by 275

Skin disease detection and segmentation using dynamic graph cut algorithm and classification through Naive Bayes classifier

Balaji, V., Suganthi, S. T., Rajadevi, R., Kumar, V. K., Balaji, B. S., & Pandiyan, S. (2020) · Measurement · doi:10.1016/j.measurement.2020.107922 · Cited by 192

An Open Framework for Remote-PPG Methods and Their Assessment

Boccignone, G., Conte, D., Cuculo, V., D’Amelio, A., Grossi, G., & Lanzarotti, R. (2020) · IEEE Access · doi:10.1109/access.2020.3040936 · Cited by 109

Deep Learning Approaches for Prognosis of Automated Skin Disease

Kshirsagar, P. R., Manoharan, H., Selvarajan, S., Alshareef, A. M., Albishry, N., & Balachandran, P. K. (2022) · Life · doi:10.3390/life12030426 · Cited by 91

BenSignNet: Bengali Sign Language Alphabet Recognition Using Concatenated Segmentation and Convolutional Neural Network

Miah, A. S. M., Shin, J., Hasan, M. A. M., & Rahim, M. A. (2022) · Applied Sciences · doi:10.3390/app12083933 · Cited by 85

Skin Disease detection based on different Segmentation Techniques

Roy, K., Chaudhuri, S. S., Ghosh, S., Dutta, S. K., Chakraborty, P., & Sarkar, R. (2019) · International Conference on Opto-Electronics and Applied Optics (Optronix) · doi:10.1109/optronix.2019.8862403 · Cited by 84

Hand Gesture Recognition Based on Auto-Landmark Localization and Reweighted Genetic Algorithm for Healthcare Muscle Activities

Ansar, H., Jalal, A., Gochoo, M., & Kim, K. (2021) · Sustainability · doi:10.3390/su13052961 · Cited by 75

A comprehensive survey on techniques to handle face identity threats: challenges and opportunities

Rusia, M. K., & Singh, D. K. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13248-6 · Cited by 74

An Exploration into Human–Computer Interaction: Hand Gesture Recognition Management in a Challenging Environment

Chang, V. I. C., Eniola, R. O., Golightly, L., & Xu, Q. A. (2023) · SN Computer Science · doi:10.1007/s42979-023-01751-y · Cited by 67

EchoHand

Wu, C., Chen, J., He, K., Zhao, Z., Du, R., & Zhang, C. (2022) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/3548606.3560553 · Cited by 66

Towards Transparency in Dermatology Image Datasets with Skin Tone Annotations by Experts, Crowds, and an Algorithm

Groh, M., Harris, C., Daneshjou, R., Badri, O., & Koochek, A. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555634 · Cited by 82

MagicHand: Interact with IoT Devices in Augmented Reality Environment

Sun, Y., Armengol-Urpi, A., Kantareddy, S. N. R., Siegel, J. E., & Sarma, S. E. (2019) · IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr.2019.8798053 · Cited by 53

Rotation, Translation and Scale Invariant Sign Word Recognition Using Deep Learning

Miah, A. S. M., Shin, J., Hasan, M. A. M., Rahim, M. A., & Okuyama, Y. (2022) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.029336 · Cited by 52

Leaf and skin disease detection using image processing

Badiger, M., Kumara, V., Shetty, S. C. N., & Poojary, S. (2022) · Global Transitions Proceedings · doi:10.1016/j.gltp.2022.03.010 · Cited by 48

Skin lesion detection based on deep neural networks

Choudhary, P., Singhai, J., & Yadav, J. S. (2022) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2022.104659 · Cited by 40

ScoreNet: deep cascade score level fusion for unconstrained ear recognition

Kaçar, Ü., & Kırcı, M. (2018) · IET Biometrics · doi:10.1049/iet-bmt.2018.5065 · Cited by 39

ClarifyNet: A high-pass and low-pass filtering based CNN for single image dehazing

Susladkar, O., Deshmukh, G., Nag, S., Mantravadi, A., Makwana, D., Ravichandran, S., Sai Chandra Teja, R., Chavhan, G. H., Mohan, C. K., & Mittal, S. (2022) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2022.102736 · Cited by 33

Real-Time Jaundice Detection in Neonates Based on Machine Learning Models

Abdulrazzak, A. Y., Mohammed, S. L., Al‐Naji, A., & Chahl, J. (2024) · BioMedInformatics · doi:10.3390/biomedinformatics4010034 · Cited by 29

Non-Local Attention and Densely-Connected Convolutional Neural Networks for Malignancy Suspiciousness Classification of Gastric Ulcer

Sun, M., Liang, K., Zhang, W., Chang, Q. H., & Zhou, X. (2020) · IEEE Access · doi:10.1109/access.2020.2967350 · Cited by 27

Unconstrained Fingerphoto Database

Chopra, S., Malhotra, A., Mayank Vatsa, A., & Singh, R. (2018) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2018.00093 · Cited by 25

A Comparison of Skin Detection Algorithms for Hand Gesture Recognition

McBride, T. J., Vandayar, N., & Nixon, K. J. (2019) · Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA) · doi:10.1109/robomech.2019.8704839 · Cited by 24

Assistive Sign Language Converter for Deaf and Dumb

Boppana, L., Ahamed, R., Rane, H., & Kodali, R. K. (2019) · IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) · doi:10.1109/ithings/greencom/cpscom/smartdata.2019.00071 · Cited by 24

Neonatal Jaundice Detection Using a Computer Vision System

Hashim, W., Al‐Naji, A., Al-Rayahi, I., Alkhaled, M., & Chahl, J. (2021) · Designs · doi:10.3390/designs5040063 · Cited by 23

Segmentation Approaches for Diabetic Foot Disorders

Arteaga-Marrero, N., Hernández-Guedes, A., Villa, E., González‐Pérez, S., Luque, C., & Ruiz‐Alzola, J. (2021) · Sensors · doi:10.3390/s21030934 · Cited by 25

Fire Detection inImages Using FrameworkBased on Image Processing, Motion Detection and Convolutional Neural Network

Taşpınar, Y. S., Köklü, M., & Altin, M. (2021) · International Journal of Intelligent Systems and Applications in Engineering · doi:10.18201/ijisae.2021473636 · Cited by 22

Color Models for Skin Lesion Classification from Dermatoscopic Images

Mporas, I., Perikos, I., & Paraskevas, M. (2020) · Smart innovation, systems and technologies · doi:10.1007/978-981-15-1918-5_5 · Cited by 22

An Enhanced Artificial Intelligence-Based Approach Applied to Vehicular Traffic Signs Detection and Road Safety Enhancement

Barodi, A., Bajit, A., Harrouti, T. E., Tamtaoui, A., & Benbrahim, M. (2021) · Advances in Science Technology and Engineering Systems Journal · doi:10.25046/aj060173 · Cited by 19

Comparative evaluation of aflatoxin and mineral binding activity of molecular imprinted polymer designed for dummy template using in vitro and in vivo models

Arak, H., Torshizi, M. A. K., Hedayati, M., & Rahimi, S. (2019) · Toxicon · doi:10.1016/j.toxicon.2019.05.005 · Cited by 19

Reduction of Motion Artifacts From Remote Photoplethysmography Using Adaptive Noise Cancellation and Modified HSI Model

Cho, D., Kim, J., Lee, K. J., & Kim, S. (2021) · IEEE Access · doi:10.1109/access.2021.3106046 · Cited by 19

Computerised prediction of healing for venous leg ulcers

Ngo, Q. C., Ogrin, R., & Kumar, D. (2022) · Scientific Reports · doi:10.1038/s41598-022-20835-y · Cited by 18

GFIE: A Dataset and Baseline for Gaze-Following from 2D to 3D in Indoor Environments

Hu, Z., Yang, Y., Zhai, X., Yang, D., Zhou, B., & Liu, J. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00860 · Cited by 19

Color-space analytics for damage detection in 3D point clouds

Dargahi, M. M., Khaloo, A., & Lattanzi, D. (2021) · Structure and Infrastructure Engineering · doi:10.1080/15732479.2021.1875488 · Cited by 17

Deep spherical harmonics light probe estimator for mixed reality games

Marques, B. A. D., Clua, E., & Vasconcelos, C. N. (2018) · Computers & Graphics · doi:10.1016/j.cag.2018.09.003 · Cited by 17

Color Invariant Skin Segmentation

Han, X., Sarkar, A., & Abbott, A. L. (2022) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw56347.2022.00328 · Cited by 16

A wearable assistive system for the visually impaired using object detection, distance measurement and tactile presentation

Chen, Y., Shen, J., & Sawada, H. (2023) · Intelligence & Robotics · doi:10.20517/ir.2023.24 · Cited by 15

Hand Gesture Recognition System for Touch-Less Car Interface Using Multiclass Support Vector Machine

Tarvekar, M. P. (2018) · International Conference on Intelligent Computing and Control Systems (ICICCS) · doi:10.1109/iccons.2018.8663003 · Cited by 15

The Landscape of Research on Skin Detectors: Coherent Taxonomy, Open Challenges, Motivations, Recommendations and Statistical Analysis, Future Directions

Chyad, M. A., Alsattar, H. A., Zaidan, B. B., Zaidan, A. A., & Shafeey, G. A. A. (2019) · IEEE Access · doi:10.1109/access.2019.2924989 · Cited by 15

Evaluating and Enhancing the Performance of Skin Disease Classification Based on Ensemble Methods

Pal, M., & Roy, B. R. (2020) · International Conference on Advanced Information and Communication Technology (ICAICT) · doi:10.1109/icaict51780.2020.9333529 · Cited by 15

A 184-μW Error-Tolerant Real-Time Hand Gesture Recognition System With Hybrid Tiny Classifiers Utilizing Edge CNN

Lu, Y., Le, V. L., & Kim, T. T.-H. (2022) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2022.3179601 · Cited by 15

The feasibility of mixed reality-based upper extremity self-training for patients with stroke—A pilot study

Ham, Y., Yang, D., Choi, Y., & Shin, J. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.994586 · Cited by 15

Study on Face Recognition Techniques

Sahu, M., & Dash, R. (2020) · doi:10.1109/iccsp48568.2020.9182358 · Cited by 14

A Study of User Interface with Wearable Devices Based on Computer Vision

Hsu, F.-R., Kuo, Y.-H., Wei, S.-Y., Hsieh, Y.-H., & Nguyen, D. C. (2019) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2019.2941463 · Cited by 14

SVBiComm: Sign-Voice Bidirectional Communication System for Normal, “Deaf/Dumb” and Blind People based on Machine Learning

Reda, M. M., Mohammed, N. G., & Seoud, R. A. A. A. A. (2018) · International Conference on Computer Applications & Information Security (ICCAIS) · doi:10.1109/cais.2018.8441985 · Cited by 13

Enhanced dynamic hand gesture recognition for finger disabilities using deep learning and an optimized Otsu threshold method

Alzeyadi, M. K. K., Der, C. S., & Chen, C. P. (2025) · Engineering Research Express · doi:10.1088/2631-8695/ada72d · Cited by 12

Real-Time FPGA Implementation of Connected Component Labelling for a 4K Video Stream

Ciarach, P., Kowalczyk, M., Przewłocka-Rus, D., & Kryjak, T. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-17227-5_13 · Cited by 12

Feature Extraction and Feature Selection for Emotion Recognition using Facial Expression

Choudhary, D., & Shukla, J. (2020) · IEEE International Conference on Multimedia Big Data · doi:10.1109/bigmm50055.2020.00027 · Cited by 12

Camera-based heart rate estimation for hospitalized newborns in the presence of motion artifacts

Chen, Q., Wang, Y., Liu, X., Long, X., Yin, B., Chen, C., & Chen, W. (2021) · BioMedical Engineering OnLine · doi:10.1186/s12938-021-00958-5 · Cited by 12

High Accuracy and Presentation Attack Resistant Hand Authentication via Acoustic Sensing for Commodity Mobile Devices

Wu, C., He, K., Chen, J., Du, R., Yan, R., & Zhao, Z. (2025) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2025.3564408 · Cited by 11

Effect of an anti-adhesion agent on vision-based assessment of cervical adhesions after thyroid surgery: randomized, placebo-controlled trial

Yu, H. W., Lee, D., Lee, K., Kim, S., Chai, Y. J., Kim, H. C., Choi, J. Y., & Lee, K. E. (2021) · Scientific Reports · doi:10.1038/s41598-021-97919-8 · Cited by 10

Weighted average pooling of deep features for tattoo identification

Nicolás-Díaz, M., Morales-González, A., & Méndez-Vázquez, H. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12516-9 · Cited by 10

Wafer particle inspection technique using computer vision based on a color space transform model

Chun, H., Wang, J., Kim, J., & Lee, C. (2023) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-023-11888-y · Cited by 10

Skin Condition Analysis of Facial Image using Smart Device: Based on Acne, Pigmentation, Flush and Blemish

Park, K., & Kim, Y.-H. (2018) · JOURNAL OF ADVANCED INFORMATION TECHNOLOGY AND CONVERGENCE · doi:10.14801/jaitc.2018.8.2.47 · Cited by 10

Image Segmentation for Skin Detection

Mohammed, S. G., Majeed, A.-R. H., Aldujaili, A. A., Hassan, E. K., & Abdul-Jabbar, S. S. (2020) · Journal of Southwest Jiaotong University · doi:10.35741/issn.0258-2724.55.1.17 · Cited by 10

Smart training: Mask R-CNN oriented approach

Su, M., Chen, J., Azzizi, V. T., Chang, H.-L., & Wei, H.-H. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115595 · Cited by 10

FairRAG: Fair Human Generation via Fair Retrieval Augmentation

Shrestha, R., Zou, Y., Chen, Q., Li, Z., Xie, Y., & Deng, S. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01140 · Cited by 15

Robotic System for Blood Serum Aliquoting Based on a Neural Network Model of Machine Vision

Khalapyan, S. Y., Rybak, L. A., Nebolsin, V., Malyshev, D. I., Nozdracheva, A., Семененко, Т. А., & Gavrilov, D. (2023) · Machines · doi:10.3390/machines11030349 · Cited by 9

Computer-Aid System for Automated Jaundice Detection

Abdulrazzak, A. Y., Mohammed, S. L., Al‐Naji, A., & Chahl, J. (2023) · Journal of Techniques · doi:10.51173/jt.v5i1.1128 · Cited by 9

Boosting hand vein recognition performance with the fusion of different color spaces in deep learning architectures

Babalola, F. O., Toygar, Ö., & Bitirim, Y. (2023) · Signal Image and Video Processing · doi:10.1007/s11760-023-02671-3 · Cited by 9

Pengenalan Motif Songket Palembang Menggunakan Deteksi Tepi Canny, PCA dan KNN

Hasan, M. A., & Liliana, D. Y. (2020) · MULTINETICS · doi:10.32722/multinetics.v6i1.2700 · Cited by 9

Color Feature Extraction of Fingernail Image based on HSV Color Space as Early Detection Risk of Diabetes Mellitus

Kurniastuti, I., Wulan, T. D., & Andini, A. (2021) · International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE) · doi:10.1109/icomitee53461.2021.9650161 · Cited by 9

RealisticHands: A Hybrid Model for 3D Hand Reconstruction

Seeber, M., Poranne, R., Polleyfeys, M., & Oswald, M. R. (2021) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv53792.2021.00013 · Cited by 9

Survey paper based critical reviews for Cosmetic Skin Diseases

Borade, S., & Kalbande, D. R. (2021) · International Conference on Artificial Intelligence and Smart Energy (ICAIS) · doi:10.1109/icais50930.2021.9395803 · Cited by 9

Development of Air Conditioner Robot Prototype That Follows Humans in Outdoor Applications

Chaari, M. Z., Abdelfatah, M., Loreno, C., & Al-Rahimi, R. (2021) · Electronics · doi:10.3390/electronics10141700 · Cited by 9

Boxing Punch Detection with Single Static Camera

Stefański, P., Jach, T., & Kozak, J. (2024) · Entropy · doi:10.3390/e26080617 · Cited by 8

Expanding Side Touch Input on Mobile Phones

Yeh, Y.-T., Roy, Q., Irudayaraj, A. A. R., & Vogel, D. (2020) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3427334 · Cited by 8

Effects of Individual Vehicle Differences on Advanced Driver-Assist System Takeover Alert Behavior

Bauchwitz, B., & Cummings, M. L. (2022) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981211068362 · Cited by 8

An Active Image Forgery Detection Approach Based on Edge Detection

MACİT, H. B., & Koyun, A. (2023) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.036216 · Cited by 8

A novel key-frame selection-based sign language recognition framework for the video data

Mangla, F. U., Bashir, A., Lali, I. U., Bukhari, A. C., & Shahzad, B. (2020) · The Imaging Science Journal · doi:10.1080/13682199.2020.1771512 · Cited by 8

Multi-audience tracking with RGB-D camera on digital signage

Low, C.-C., Ong, L.-Y., Koo, V. C., & Leow, M.-C. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e05107 · Cited by 8

Spying through Virtual Backgrounds of Video Calls

Hilgefort, J. M., Arp, D., & Rieck, K. (2021) · ACM Workshop on Artificial Intelligence and Security (AISec) · doi:10.1145/3474369.3486870 · Cited by 8

Deep Leaning Based Static Indian-Gujarati Sign Language Gesture Recognition

Patel, D. U., & Joshi, J. M. (2022) · SN Computer Science · doi:10.1007/s42979-022-01254-2 · Cited by 8

Skin-Tone and Occasion Oriented Outfit Recommendation SystemPreprint

Garude, D., Khopkar, A., Dhake, M., Laghane, S., & Maktum, T. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3368058 · Cited by 8

Effective Acne Detection using Component Image a* of CIE L*a*b* Color Space

Park, K.-H., & Noh, H. (2018) · Journal of Digital Contents Society · doi:10.9728/dcs.2018.19.7.1397 · Cited by 7

Human Skin Color Detection Technique Using Different Color Models

Khanam, R., Johri, P., & Diván, M. J. (2021) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-75945-2_14 · Cited by 7

Skin color classification of Koreans using clustering

Kye, S., & Lee, O. (2022) · Skin Research and Technology · doi:10.1111/srt.13201 · Cited by 7

Skin Disease Detection and Classification Using ResNet-50 and Support Vector Machine: An Effective Approach for Dermatological Diagnosis

Gaffoor, N., & Soomro, S. (2023) · IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) · doi:10.1109/iotais60147.2023.10346059 · Cited by 10

Evaluation of different chrominance models in the detection and reconstruction of faces and hands using the growing neural gas network

Angelopoulou, A., García‐Rodríguez, J., Orts‐Escolano, S., Kapetanios, E., Liang, X. Z., Woll, B., & Ψαρρού, Α. (2019) · Pattern Analysis and Applications · doi:10.1007/s10044-019-00819-x · Cited by 7

A Comparative Study of Tools for Explicit Content Detection in Images

Dubettier, A., Gernot, T., Giguet, E., & Rosenberger, C. (2023) · 2023 International Conference on Cyberworlds (CW) · doi:10.1109/cw58918.2023.00077 · Cited by 5

A 3D Approach for the Virtual Commissioning of Processing Plants

Striffler, N., & Voigt, T. (2025) · IEEE Access · doi:10.1109/access.2025.3536088 · Cited by 6

Automated Melanoma Types and Stages Classification for dermoscopy images

Parmar, B., & Talati, B. J. (2019) · Innovations in Power and Advanced Computing Technologies (i-PACT) · doi:10.1109/i-pact44901.2019.8960137 · Cited by 6

Simple Hybrid Camera-Based System Using Two Views for Three-Dimensional Body Measurements

Montazerian, M., & Leymarie, F. F. (2023) · Symmetry · doi:10.3390/sym16010049 · Cited by 6

Human Skin Colour Detection Using Bayesian Rough Decision Tree

Abbas, A. R., & Farooq, A. O. (2018) · Communications in computer and information science · doi:10.1007/978-3-030-01653-1_15 · Cited by 6

Recognizing Indonesian Sign Language Gestures Using Features Generated by Elliptical Model Tracking and Angular Projection

Adimas, D. M., Rakun, E., & Hardianto, D. (2019) · Intelligent Autonomous Systems · doi:10.1109/icoias.2019.00011 · Cited by 6

Introduction to Image Color Feature

Chaki, J., & Dey, N. (2020) · SpringerBriefs in applied sciences and technology · doi:10.1007/978-981-15-5761-3_1 · Cited by 6

Infants scan static and dynamic facial expressions differently

Prunty, J. E., Keemink, J. R., & Kelly, D. J. (2021) · Infancy · doi:10.1111/infa.12426 · Cited by 6

An Intelligent HealthCare Monitoring Framework for Daily Assistant Living

Ghadi, Y. Y., Khalid, N., Alsuhibany, S. A., Shloul, T. A., Jalal, A., & Park, J. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.024422 · Cited by 7

LGF-SLR: Hand Local–Global Fusion Network for Skeleton-Based Sign Language Recognition

Gao, Q. H., Zhang, M., & Ju, Z. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3527198 · Cited by 5

Taxonomical classification of reef fish with broadband backscattering models and machine learning approaches

Roa, C., Pedersen, G., Bollinger, M., Taylor, J. C., & Boswell, K. M. (2022) · The Journal of the Acoustical Society of America · doi:10.1121/10.0012192 · Cited by 5

User Authentication via Finger-Selfies

Malhotra, A., Chopra, S., Mayank Vatsa, A., & Singh, R. (2019) · Advances in computer vision and pattern recognition · doi:10.1007/978-3-030-26972-2_2 · Cited by 5

Detection of Jaundice in Neonates Using Artificial Intelligence

Nihila, S., Rajalakshmi, T., Panda, S. S., Lhazay, N., & Giri, G. D. (2021) · Advances in intelligent systems and computing · doi:10.1007/978-981-16-1696-9_41 · Cited by 5

PKT: fast color-based spatial model for human skin detection

Samson, G. L., & Lu, J. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-10955-4 · Cited by 5

Experimental Study on Multiple Face Detection with Depth and Skin Color

Low, C.-C., Ong, L.-Y., & Koo, V. C. (2019) · IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE) · doi:10.1109/iscaie.2019.8743890 · Cited by 5

Maize Leaf Images Segmentation Using Color Threshold and K-means Clustering Methods to Identify the Percentage of the Affected Areas

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