Optics and Precision Engineering, Volume. 32, Issue 8, 1241(2024)
Dense control valve parts dataset for industrial object detection
[1] X Y SUN, S S YANG, C ZHAO. Lightweight industrial image classifier based on federated few-shot learning. IEEE Transactions on Industrial Informatics, 19, 7367-7376(2023).
[2] A AGGARWAL, V KUMAR, R GUPTA. Object detection based approaches in image classification: a brief overview, 1-6(2023).
[3] G YASMINE, G MAHA, M HICHAM. Overview of single-stage object detection models: from yolov1 to Yolov7, 1579-1584(2023).
[4] [4] 庄存波, 刘检华, 隋秀峰, 等. 工业互联网推动离散制造业转型升级的发展现状、技术体系及应用挑战[J]. 计算机集成制造系统, 2019, 25(12): 3061-3069. doi: 10.13196/j.cims.2019.12.008ZHUANGC B, LIUJ H, SUIX F, et al. Status, technical architecture and application challenges for transformation and updating of discrete manufacturing industry driven by industrial Internet[J]. Computer Integrated Manufacturing Systems, 2019, 25(12): 3061-3069.(in Chinese). doi: 10.13196/j.cims.2019.12.008
[5] Y T WANG, W W SHEN. Mechanical parts detection algorithm based on enhanced faster R-CNN, 4348-4353(2021).
[6] M EVERINGHAM, ESLAMI S MALI, L VAN GOOL et al. The pascal visual object classes challenge: a retrospective. International Journal of Computer Vision, 111, 98-136(2015).
[7] T Y LIN, M MAIRE, S BELONGIE et al.
[8] A KUZNETSOVA, N ALLDRIN et al. The open images dataset V4. International Journal of Computer Vision, 128, 1956-1981(2020).
[9] J DENG, W DONG, R SOCHER et al. ImageNet: a large-scale hierarchical image database, 248-255(2009).
[10] B DROST, M ULRICH, P BERGMANN et al. Introducing MVTec ITODD-a dataset for 3D object recognition in industry, 2200-2208(2017).
[11] T HODAN, P HALUZA, Š OBDRŽÁLEK et al. T-LESS: an RGB-D dataset for 6D pose estimation of texture-less objects, 880-888(2017).
[12] D TABERNIK, S ŠELA, J SKVARČ et al. Segmentation-based deep-learning approach for surface-defect detection. Journal of Intelligent Manufacturing, 31, 759-776(2020).
[13] S KHALILIAN, Y HALLAJ, A BALOUCHESTANI et al. PCB defect detection using denoising convolutional autoencoders, 1-5(2020).
[14] Y HE, K C SONG, Q G MENG et al. An end-to-end steel surface defect detection approach via fusing multiple hierarchical features. IEEE Transactions on Instrumentation and Measurement, 69, 1493-1504(2020).
[15] H X CHEN, Y Z DU, Y Q FU et al. DCAM-net: a rapid detection network for strip steel surface defects based on deformable convolution and attention mechanism. IEEE Transactions on Instrumentation and Measurement, 72, 5005312(2023).
[16] W Y WANG, C F MI, Z H WU et al. A real-time steel surface defect detection approach with high accuracy. IEEE Transactions on Instrumentation and Measurement, 71, 5005610(2021).
[17] [17] 郭峰, 朱启兵, 黄敏, 等. 基于改进YOLOV4的陶瓷基板瑕疵检测[J]. 光学 精密工程, 2022, 30(13): 1631-1641. doi: 10.37188/OPE.20223013.1631GUOF, ZHUQ B, HUANGM, et al. Defect detection in ceramic substrate based on improved YOLOV4[J]. Opt. Precision Eng., 2022, 30(13): 1631-1641.(in Chinese). doi: 10.37188/OPE.20223013.1631
[18] [18] 李宝平, 戚恒熠, 王满利, 等. 联合3D建模与改进CycleGAN的故障数据集扩增方法[J]. 光学 精密工程, 2023, 31(16): 2406-2417. doi: 10.37188/ope.20233116.2406LIB P, QIH Y, WANGM L, et al. Equipment fault dataset amplification method combine 3D model with improved CycleGAN[J]. Opt. Precision Eng., 2023, 31(16): 2406-2417.(in Chinese). doi: 10.37188/ope.20233116.2406
[19] W CHEN, J ZHAO, W L ZHAO et al. Shape-aware monocular 3D object detection. IEEE Transactions on Intelligent Transportation Systems, 24, 6416-6424(2023).
[20] G S XIA, X BAI, J DING et al. DOTA: a large-scale dataset for object detection in aerial images, 3974-3983(2018).
[21] H CHEN, Z W SHI. A spatial-temporal attention-based method and a new dataset for remote sensing image change detection. Remote Sensing, 12, 1662(2020).
[22] S Q REN, K M HE, R GIRSHICK et al. Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).
[23] W LIU, D ANGUELOV, D ERHAN et al.
[24] N CARION, F MASSA, G SYNNAEVE et al.
[25] J REDMON, A FARHADI. YOLOv3: an incremental improvement(2018).
Get Citation
Copy Citation Text
Linyi WANG, Jing BAI, Yanmei LI, Wenjing LI. Dense control valve parts dataset for industrial object detection[J]. Optics and Precision Engineering, 2024, 32(8): 1241
Category:
Received: Sep. 22, 2023
Accepted: --
Published Online: May. 29, 2024
The Author Email: BAI Jing (baijing_nun@163. com)