2d object detection with transformers: a review

T Shehzadi, KA Hashmi, D Stricker, MZ Afzal - arXiv preprint arXiv …, 2023 - arxiv.org
Astounding performance of Transformers in natural language processing (NLP) has
delighted researchers to explore their utilization in computer vision tasks. Like other …

More than encoder: Introducing transformer decoder to upsample

Y Li, W Cai, Y Gao, C Li, X Hu - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Medical image segmentation methods downsample images for feature extraction and then
upsample them to restore resolution for pixel-level predictions. In such schema, upsample …

Revisiting class imbalance for end-to-end semi-supervised object detection

P Kar, V Chudasama, N Onoe… - Proceedings of the …, 2023 - openaccess.thecvf.com
Semi-supervised object detection (SSOD) has made significant progress with the
development of pseudo-label-based end-to-end methods. However, many of these methods …

Enhancing prospective consistency for semi-supervised object detection in remote sensing images

J Shen, C Zhang, Y Yuan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep-learning-based object detection has recently played a vital role in both computer
vision and Earth observation communities. However, the performance of modern object …

Towards Enhanced Analysis of Lung Cancer Lesions in EBUS-TBNA--A Semi-Supervised Video Object Detection Method

JA Lin, YC Cheng, CK Lin - arXiv preprint arXiv:2404.01929, 2024 - arxiv.org
This study aims to establish a computer-aided diagnostic system for lung lesions using
bronchoscope endobronchial ultrasound (EBUS) to assist physicians in identifying lesion …