output
20132026
most citedCovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection

779 citations

Showing 2025 · cs.CVShow all

8 papers · 2 filters

cs.CV2025

Residual-SwinCA-Net: A Channel-Aware Integrated Residual CNN-Swin Transformer for Malignant Lesion Segmentation in BUSI

Saeeda Naz, Saddam Hussain Khan

A novel deep hybrid Residual-SwinCA-Net segmentation framework is proposed in the study for addressing such challenges by extracting locally correlated and robust features, incorpo…

cs.CV2025★ 11 cited

Human Motion Video Generation: A Survey

Haiwei Xue, Xiangyang Luo, Zhanghao Hu +12

Human motion video generation has garnered significant research interest due to its broad applications, enabling innovations such as photorealistic singing heads or dynamic avatars…

cs.CV2025★ 1 cited

A fine-grained attention and geometric correspondence model for musculoskeletal risk classification in athletes using multimodal visual and skeletal features

Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Tamanna Shermin +3

Musculoskeletal disorders pose significant risks to athletes, and early risk assessment is essential for prevention. However, most existing methods are designed for controlled sett…

cs.CV2025★ 4 cited

Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge

Tobias Rueckert, David Rauber, Raphaela Maerkl +58

Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minim…

cs.CV2025★ 4 cited

ACMamba: Fast Unsupervised Anomaly Detection via An Asymmetrical Consensus State Space Model

Guanchun Wang, Xiangrong Zhang, Yifei Zhang +4

Unsupervised anomaly detection in hyperspectral images (HSI), aiming to detect unknown targets from backgrounds, is challenging for earth surface monitoring. However, current studi…

cs.CV2025

A Comprehensive Survey on Architectural Advances in Deep CNNs: Challenges, Applications, and Emerging Research Directions

Saddam Hussain Khan, Rashid Iqbal

Deep Convolutional Neural Networks (CNNs) have significantly advanced deep learning, driving breakthroughs in computer vision, natural language processing, medical diagnosis, objec…