Tianxiao Zhang

 Selected Publications

• Zhang, T., Xu, W., Luo, B. and Wang, G., 2025. Depth-Wise Convolutions in Vision Transformers for efficient training on small datasets. Neurocomputing, 617, p.128998.
• Li, K., Zhang, T., Peng, K.C. and Wang, G., 2025. PF3Det: A Prompted Foundation Feature Assisted Visual LiDAR 3D Detector. In Proceedings of the Computer Vision and Pattern Recognition Conference (pp. 3778-3787).
• Li, K., Zhang, T., Zhong, C., Zhang, Z. and Wang, G., 2025. Robust 3D point clouds classification based on declarative defenders. Neural Computing and Applications, 37(3), pp.1209-1221.
• Rahman, R., Indris, C., Bramesfeld, G., Zhang, T., Li, K., Chen, X., Grijalva, I., McCornack, B., Flippo, D., Sharda, A. and Wang, G., 2024. A new dataset and comparative study for aphid cluster detection and segmentation in sorghum fields. Journal of Imaging, 10(5), p.114.
• Bur, A.M., Zhang, T., Chen, X., Kavookjian, H., Kraft, S., Karadaghy, O., Farrokhian, N., Mussatto, C., Penn, J. and Wang, G., 2023. Interpretable computer vision to detect and classify structural laryngeal lesions in digital flexible laryngoscopic images. Otolaryngology–Head and Neck Surgery, 169(6), pp.1564-1572.
• Zhang, T., Li, K., Chen, X., Zhong, C., Luo, B., Grijalva, I., McCornack, B., Flippo, D., Sharda, A. and Wang, G., 2023. Aphid cluster recognition and detection in the wild using deep learning models. Scientific Reports, 13(1), p.13410.
• Zhang, T., Bur, A.M., Kraft, S., Kavookjian, H., Renslo, B., Chen, X., Luo, B. and Wang, G., 2023. Gender, smoking history, and age prediction from laryngeal images. Journal of imaging, 9(6), p.109.
• Rahman, R., Indris, C., Zhang, T., Li, K., McCornack, B., Flippo, D., Sharda, A. and Wang, G., 2023. On the real-time semantic segmentation of aphid clusters in the wild. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 6299-6306).
• Zhang, T., Luo, B., Sharda, A. and Wang, G., 2022. Dynamic label assignment for object detection by combining predicted ious and anchor ious. Journal of Imaging, 8(7), p.193.
• Yang, Y., Zhang, T., Li, G., Kim, T. and Wang, G., 2022. An unsupervised domain adaptation model based on dual-module adversarial training. Neurocomputing, 475, pp.102-111.
• Li, K., Fathan, M.I., Patel, K., Zhang, T., Zhong, C., Bansal, A., Rastogi, A., Wang, J.S. and Wang, G., 2021. Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations. Plos one, 16(8), p.e0255809.
• Zhang, T., Ma, W. and Wang, G., 2021, August. Six-channel image representation for cross-domain object detection. In International Conference on Image and Graphics (pp. 171-184). Cham: Springer International Publishing.
• Zhang, X., Zhang, T., Yang, Y., Wang, Z. and Wang, G., 2020, October. Real-time golf ball detection and tracking based on convolutional neural networks. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2808-2813). IEEE.