This work is licensed under the Creative Commons Attribution 4.0 International License.
Banos, O., Galvez, J.-M., Damas, M., Pomares, H., & Rojas, I. (2014). Window size impact in human activity recognition. Sensors, 14(4), 6474-6499.BanosO.GalvezJ.-M.DamasM.PomaresH. & RojasI. (2014). Window size impact in human activity recognition. Sensors, 14(4), 6474-6499.Search in Google Scholar
Chen, Z., Xu, Q., Cong, R., & Huang, Q. (2020). Global context-aware progressive aggregation network for salient object detection. Proceedings of the AAAI conference on artificial intelligence.ChenZ.XuQ.CongR. & HuangQ. (2020). Global context-aware progressive aggregation network for salient object detection. Proceedings of the AAAI conference on artificial intelligence.Search in Google Scholar
Feng, M., Lu, H., & Ding, E. (2019). Attentive feedback network for boundary-aware salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.FengM.LuH. & DingE. (2019). Attentive feedback network for boundary-aware salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.Search in Google Scholar
Ghosh, I., Ramasamy Ramamurthy, S., Chakma, A., & Roy, N. (2023). Sports analytics review: Artificial intelligence applications, emerging technologies, and algorithmic perspective. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(5), e1496.GhoshI.Ramasamy RamamurthyS.ChakmaA. & RoyN. (2023). Sports analytics review: Artificial intelligence applications, emerging technologies, and algorithmic perspective. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(5), e1496.Search in Google Scholar
Hao, M., Zhang, Z., Li, L., Dong, K., Cheng, L., Tiwari, P., & Ning, X. (2024). Coarse to fine-based image–point cloud fusion network for 3D object detection. Information Fusion, 112, 102551.HaoM.ZhangZ.LiL.DongK.ChengL.TiwariP. & NingX. (2024). Coarse to fine-based image–point cloud fusion network for 3D object detection. Information Fusion, 112, 102551.Search in Google Scholar
Henriksen, A., Haugen Mikalsen, M., Woldaregay, A. Z., Muzny, M., Hartvigsen, G., Hopstock, L. A., & Grimsgaard, S. (2018). Using fitness trackers and smartwatches to measure physical activity in research: analysis of consumer wrist-worn wearables. Journal of medical Internet research, 20(3), e110.HenriksenA.Haugen MikalsenM.WoldaregayA. Z.MuznyM.HartvigsenG.HopstockL. A. & GrimsgaardS. (2018). Using fitness trackers and smartwatches to measure physical activity in research: analysis of consumer wrist-worn wearables. Journal of medical Internet research, 20(3), e110.Search in Google Scholar
Hou, Q., Cheng, M.-M., Hu, X., Borji, A., Tu, Z., & Torr, P. H. (2017). Deeply supervised salient object detection with short connections. Proceedings of the IEEE conference on computer vision and pattern recognition.HouQ.ChengM.-M.HuX.BorjiA.TuZ. & TorrP. H. (2017). Deeply supervised salient object detection with short connections. Proceedings of the IEEE conference on computer vision and pattern recognition.Search in Google Scholar
Hu, S., Chen, X., Ni, W., Hossain, E., & Wang, X. (2021). Distributed machine learning for wireless communication networks: Techniques, architectures, and applications. IEEE Communications Surveys & Tutorials, 23(3), 1458-1493.HuS.ChenX.NiW.HossainE. & WangX. (2021). Distributed machine learning for wireless communication networks: Techniques, architectures, and applications. IEEE Communications Surveys & Tutorials, 23(3), 1458-1493.Search in Google Scholar
Huang, C., & Xu, Y. (2023). Psychological factors of sports injury caused by wireless communication of embedded microprocessor in social sports teaching and training. Wireless Networks, 29(3), 1411-1419.HuangC. & XuY. (2023). Psychological factors of sports injury caused by wireless communication of embedded microprocessor in social sports teaching and training. Wireless Networks, 29(3), 1411-1419.Search in Google Scholar
Jayal, A., McRobert, A., Oatley, G., & O’Donoghue, P. (2018). Sports analytics: Analysis, visualisation and decision making in sports performance. Routledge.JayalA.McRobertA.OatleyG. & O’DonoghueP. (2018). Sports analytics: Analysis, visualisation and decision making in sports performance. Routledge.Search in Google Scholar
Jin, L., Zhang, G., Wang, Y., & Li, S. (2022). RNN-based quadratic programming scheme for tennis-training robots with flexible capabilities. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(2), 838-847.JinL.ZhangG.WangY. & LiS. (2022). RNN-based quadratic programming scheme for tennis-training robots with flexible capabilities. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(2), 838-847.Search in Google Scholar
Liu, J.-J., Hou, Q., Cheng, M.-M., Feng, J., & Jiang, J. (2019). A simple pooling-based design for real-time salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.LiuJ.-J.HouQ.ChengM.-M.FengJ. & JiangJ. (2019). A simple pooling-based design for real-time salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.Search in Google Scholar
Liu, N., Han, J., & Yang, M.-H. (2018). Picanet: Learning pixel-wise contextual attention for saliency detection. Proceedings of the IEEE conference on computer vision and pattern recognition.LiuN.HanJ. & YangM.-H. (2018). Picanet: Learning pixel-wise contextual attention for saliency detection. Proceedings of the IEEE conference on computer vision and pattern recognition.Search in Google Scholar
Liu, Y., Zhang, D., Zhang, Q., & Han, J. (2021). Part-object relational visual saliency. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7), 3688-3704.LiuY.ZhangD.ZhangQ. & HanJ. (2021). Part-object relational visual saliency. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7), 3688-3704.Search in Google Scholar
Luo, J., Gao, W., & Wang, Z. L. (2021). The triboelectric nanogenerator as an innovative technology toward intelligent sports. Advanced Materials, 33(17), 2004178.LuoJ.GaoW. & WangZ. L. (2021). The triboelectric nanogenerator as an innovative technology toward intelligent sports. Advanced Materials, 33(17), 2004178.Search in Google Scholar
Ning, X., Yu, Z., Li, L., Li, W., & Tiwari, P. (2024). DILF: Differentiable rendering-based multi-view Image–Language Fusion for zero-shot 3D shape understanding. Information Fusion, 102, 102033.NingX.YuZ.LiL.LiW. & TiwariP. (2024). DILF: Differentiable rendering-based multi-view Image–Language Fusion for zero-shot 3D shape understanding. Information Fusion, 102, 102033.Search in Google Scholar
Nybo, L., Sundstrup, E., Jakobsen, M. D., Mohr, M., Hornstrup, T., Simonsen, L., Bülow, J., Randers, M. B., Nielsen, J. J., & Aagaard, P. (2010). High-intensity training versus traditional exercise interventions for promoting health. Medicine & Science in Sports & Exercise, 42(10), 1951-1958.NyboL.SundstrupE.JakobsenM. D.MohrM.HornstrupT.SimonsenL.BülowJ.RandersM. B.NielsenJ. J. & AagaardP. (2010). High-intensity training versus traditional exercise interventions for promoting health. Medicine & Science in Sports & Exercise, 42(10), 1951-1958.Search in Google Scholar
Pang, Y., Zhao, X., Zhang, L., & Lu, H. (2020). Multi-scale interactive network for salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.PangY.ZhaoX.ZhangL. & LuH. (2020). Multi-scale interactive network for salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.Search in Google Scholar
Paterakis, N. G., Mocanu, E., Gibescu, M., Stappers, B., & van Alst, W. (2017). Deep learning versus traditional machine learning methods for aggregated energy demand prediction. 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe).PaterakisN. G.MocanuE.GibescuM.StappersB. & van AlstW. (2017). Deep learning versus traditional machine learning methods for aggregated energy demand prediction. 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe).Search in Google Scholar
Peng, X., Xu, Q., Feng, Z., Zhao, H., Tan, L., Zhou, Y., Zhang, Z., Gong, C., & Zheng, Y. (2024). Automatic News Generation and Fact-Checking System Based on Language Processing. arXiv preprint arXiv:2405.10492.PengX.XuQ.FengZ.ZhaoH.TanL.ZhouY.ZhangZ.GongC. & ZhengY. (2024). Automatic News Generation and Fact-Checking System Based on Language Processing. arXiv preprint arXiv:2405.10492.Search in Google Scholar
Qin, X., Zhang, Z., Huang, C., Gao, C., Dehghan, M., & Jagersand, M. (2019). Basnet: Boundary-aware salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. Numerical simulation and optimization method of sports teaching and training based on embedded wireless communication networkQinX.ZhangZ.HuangC.GaoC.DehghanM. & JagersandM. (2019). Basnet: Boundary-aware salient object detection. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. Numerical simulation and optimization method of sports teaching and training based on embedded wireless communication networkSearch in Google Scholar
Qiu, Y., Liu, Y., Chen, Y., Zhang, J., Zhu, J., & Xu, J. (2022). A2SPPNet: Attentive atrous spatial pyramid pooling network for salient object detection. IEEE Transactions on Multimedia, 25, 1991-2006.QiuY.LiuY.ChenY.ZhangJ.ZhuJ. & XuJ. (2022). A2SPPNet: Attentive atrous spatial pyramid pooling network for salient object detection. IEEE Transactions on Multimedia, 25, 1991-2006.Search in Google Scholar
Rahman, S. A., & Adjeroh, D. A. (2019). Deep learning using convolutional LSTM estimates biological age from physical activity. Scientific Reports, 9(1), 11425.RahmanS. A. & AdjerohD. A. (2019). Deep learning using convolutional LSTM estimates biological age from physical activity. Scientific Reports, 9(1), 11425.Search in Google Scholar
Rana, M., & Mittal, V. (2020). Wearable sensors for real-time kinematics analysis in sports: A review. IEEE Sensors Journal, 21(2), 1187-1207.RanaM. & MittalV. (2020). Wearable sensors for real-time kinematics analysis in sports: A review. IEEE Sensors Journal, 21(2), 1187-1207.Search in Google Scholar
Rehman, S. U., Tu, S., Rehman, O. U., Huang, Y., Magurawalage, C. M. S., & Chang, C.-C. (2018). Optimization of CNN through novel training strategy for visual classification problems. Entropy, 20(4), 290.RehmanS. U.TuS.RehmanO. U.HuangY.MagurawalageC. M. S. & ChangC.-C. (2018). Optimization of CNN through novel training strategy for visual classification problems. Entropy, 20(4), 290.Search in Google Scholar
Reiss, A., & Stricker, D. (2012). Introducing a new benchmarked dataset for activity monitoring. 2012 16th International Symposium on Wearable Computers.ReissA. & StrickerD. (2012). Introducing a new benchmarked dataset for activity monitoring. 2012 16th International Symposium on Wearable Computers.Search in Google Scholar
Schneider, C., Hanakam, F., Wiewelhove, T., Döweling, A., Kellmann, M., Meyer, T., Pfeiffer, M., & Ferrauti, A. (2018). Heart rate monitoring in team sports—a conceptual framework for contextualizing heart rate measures for training and recovery prescription. Frontiers in Physiology, 9, 639.SchneiderC.HanakamF.WiewelhoveT.DöwelingA.KellmannM.MeyerT.PfeifferM. & FerrautiA. (2018). Heart rate monitoring in team sports—a conceptual framework for contextualizing heart rate measures for training and recovery prescription. Frontiers in Physiology, 9, 639.Search in Google Scholar
Soltani, P., & Morice, A. H. (2020). Augmented reality tools for sports education and training. Computers & Education, 155, 103923.SoltaniP. & MoriceA. H. (2020). Augmented reality tools for sports education and training. Computers & Education, 155, 103923.Search in Google Scholar
Wang, J., Ma, J., Hu, K., Zhou, Z., Zhang, H., Xie, X., & Wu, Y. (2022). Tac-trainer: A visual analytics system for IoT-based racket sports training. IEEE Transactions on Visualization and Computer Graphics, 29(1), 951-961.WangJ.MaJ.HuK.ZhouZ.ZhangH.XieX. & WuY. (2022). Tac-trainer: A visual analytics system for IoT-based racket sports training. IEEE Transactions on Visualization and Computer Graphics, 29(1), 951-961.Search in Google Scholar
Wang, T., & Park, J. (2021). Design and implementation of intelligent sports training system for college students’ mental health education. Frontiers in Psychology, 12, 634978.WangT. & ParkJ. (2021). Design and implementation of intelligent sports training system for college students’ mental health education. Frontiers in Psychology, 12, 634978.Search in Google Scholar
Wang, T., Zhang, L., Wang, S., Lu, H., Yang, G., Ruan, X., & Borji, A. (2018). Detect globally, refine locally: A novel approach to saliency detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.WangT.ZhangL.WangS.LuH.YangG.RuanX. & BorjiA. (2018). Detect globally, refine locally: A novel approach to saliency detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Search in Google Scholar
Wang, Y., Chen, M., Wang, X., Chan, R. H., & Li, W. J. (2018). IoT for next-generation racket sports training. IEEE Internet of Things Journal, 5(6), 4558-4566.WangY.ChenM.WangX.ChanR. H. & LiW. J. (2018). IoT for next-generation racket sports training. IEEE Internet of Things Journal, 5(6), 4558-4566.Search in Google Scholar
Wei, J., Wang, S., Wu, Z., Su, C., Huang, Q., & Tian, Q. (2020). Label decoupling framework for salient object detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.WeiJ.WangS.WuZ.SuC.HuangQ. & TianQ. (2020). Label decoupling framework for salient object detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.Search in Google Scholar
Wei, S., Wang, K., & Li, X. (2022). Design and implementation of college sports training system based on artificial intelligence. International Journal of System Assurance Engineering and Management, 13(Suppl 3), 971-977.WeiS.WangK. & LiX. (2022). Design and implementation of college sports training system based on artificial intelligence. International Journal of System Assurance Engineering and Management, 13(Suppl 3), 971-977.Search in Google Scholar
Wu, Z., Su, L., & Huang, Q. (2019). Cascaded partial decoder for fast and accurate salient object detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.WuZ.SuL. & HuangQ. (2019). Cascaded partial decoder for fast and accurate salient object detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.Search in Google Scholar
Xu, B., Liang, H., Liang, R., & Chen, P. (2021). Locate globally, segment locally: A progressive architecture with knowledge review network for salient object detection. Proceedings of the AAAI Conference on Artificial Intelligence.XuB.LiangH.LiangR. & ChenP. (2021). Locate globally, segment locally: A progressive architecture with knowledge review network for salient object detection. Proceedings of the AAAI Conference on Artificial Intelligence.Search in Google Scholar
Xu, Y., Xu, D., Hong, X., Ouyang, W., Ji, R., Xu, M., & Zhao, G. (2019). Structured modeling of joint deep feature and prediction refinement for salient object detection. Proceedings of the IEEE/CVF International Conference on Computer Vision.XuY.XuD.HongX.OuyangW.JiR.XuM. & ZhaoG. (2019). Structured modeling of joint deep feature and prediction refinement for salient object detection. Proceedings of the IEEE/CVF International Conference on Computer Vision.Search in Google Scholar
Yang, L., Lu, K., Diaz-Olivares, J. A., Seoane, F., Lindecrantz, K., Forsman, M., Abtahi, F., & Eklund, J. A. (2018). Towards smart work clothing for automatic risk assessment of physical workload. IEEE Access, 6, 40059-40072.YangL.LuK.Diaz-OlivaresJ. A.SeoaneF.LindecrantzK.ForsmanM.AbtahiF. & EklundJ. A. (2018). Towards smart work clothing for automatic risk assessment of physical workload. IEEE Access, 6, 40059-40072.Search in Google Scholar
Zeng, Y., Zhang, P., Zhang, J., Lin, Z., & Lu, H. (2019). Towards high-resolution salient object detection. Proceedings of the IEEE/CVF International Conference on Computer Vision.ZengY.ZhangP.ZhangJ.LinZ. & LuH. (2019). Towards high-resolution salient object detection. Proceedings of the IEEE/CVF International Conference on Computer Vision.Search in Google Scholar
Zhang, D., Tian, H., & Han, J. (2020). Few-cost salient object detection with adversarial-paced learning. Advances in Neural Information Processing Systems, 33, 12236-12247.ZhangD.TianH. & HanJ. (2020). Few-cost salient object detection with adversarial-paced learning. Advances in Neural Information Processing Systems, 33, 12236-12247.Search in Google Scholar
Zhang, H., Wang, C., Yu, L., Tian, S., Ning, X., & Rodrigues, J. (2024). PointGT: A method for point-cloud classification and segmentation based on local geometric transformation. IEEE Transactions on Multimedia.ZhangH.WangC.YuL.TianS.NingX. & RodriguesJ. (2024). PointGT: A method for point-cloud classification and segmentation based on local geometric transformation. IEEE Transactions on Multimedia.Search in Google Scholar
Zhang, H., Yang, J., Qian, J., Gong, C., Ning, X., Zha, Z., & Wen, B. (2024). Faster nonconvex low-rank matrix learning for image low-level and high-level vision: A unified framework. Information Fusion, 108, 102347.ZhangH.YangJ.QianJ.GongC.NingX.ZhaZ. & WenB. (2024). Faster nonconvex low-rank matrix learning for image low-level and high-level vision: A unified framework. Information Fusion, 108, 102347.Search in Google Scholar
Zhang, Q., Zhang, X., Hu, H., Li, C., Lin, Y., & Ma, R. (2022). Sports match prediction model for training and exercise using attention-based LSTM network. Digital Communications and Networks, 8(4), 508-515.ZhangQ.ZhangX.HuH.LiC.LinY. & MaR. (2022). Sports match prediction model for training and exercise using attention-based LSTM network. Digital Communications and Networks, 8(4), 508-515.Search in Google Scholar
Zhang, X. (2021). Application of human motion recognition utilizing deep learning and smart wearable device in sports. International Journal of System Assurance Engineering and Management, 12(4), 835-843.ZhangX. (2021). Application of human motion recognition utilizing deep learning and smart wearable device in sports. International Journal of System Assurance Engineering and Management, 12(4), 835-843.Search in Google Scholar
Zhao, X., Pang, Y., Zhang, L., Lu, H., & Zhang, L. (2020). Suppress and balance: A simple gated network for salient object detection. Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16.ZhaoX.PangY.ZhangL.LuH. & ZhangL. (2020). Suppress and balance: A simple gated network for salient object detection. Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16.Search in Google Scholar
Zhou, H., Xie, X., Lai, J.-H., Chen, Z., & Yang, L. (2020). Interactive two-stream decoder for accurate and fast saliency detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.ZhouH.XieX.LaiJ.-H.ChenZ. & YangL. (2020). Interactive two-stream decoder for accurate and fast saliency detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.Search in Google Scholar
Zhou, Y., Wang, Z., Zheng, S., Zhou, L., Dai, L., Luo, H., Zhang, Z., & Sui, M. (2024). Optimization of automated garbage recognition model based on ResNet-50 and weakly supervised CNN for sustainable urban development. Alexandria Engineering Journal, 108, 415-427.ZhouY.WangZ.ZhengS.ZhouL.DaiL.LuoH.ZhangZ. & SuiM. (2024). Optimization of automated garbage recognition model based on ResNet-50 and weakly supervised CNN for sustainable urban development. Alexandria Engineering Journal, 108, 415-427.Search in Google Scholar
Zou, H., Yu, R., Anand, R., Tong, J., & Huang, A. Q. (2023). A GAN variable-frequency series resonant dual-active-bridge bidirectional ac-dc converter for battery energy storage system. 2023 IEEE Applied Power Electronics Conference and Exposition (APEC).ZouH.YuR.AnandR.TongJ. & HuangA. Q. (2023). A GAN variable-frequency series resonant dual-active-bridge bidirectional ac-dc converter for battery energy storage system. 2023 IEEE Applied Power Electronics Conference and Exposition (APEC).Search in Google Scholar