Advances in medical image analysis with vision transformers: a comprehensive review
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …
has recently also triggered broad interest in Computer Vision. Among other merits …
Efficientformer: Vision transformers at mobilenet speed
Abstract Vision Transformers (ViT) have shown rapid progress in computer vision tasks,
achieving promising results on various benchmarks. However, due to the massive number of …
achieving promising results on various benchmarks. However, due to the massive number of …
Rethinking vision transformers for mobilenet size and speed
With the success of Vision Transformers (ViTs) in computer vision tasks, recent arts try to
optimize the performance and complexity of ViTs to enable efficient deployment on mobile …
optimize the performance and complexity of ViTs to enable efficient deployment on mobile …
Next-vit: Next generation vision transformer for efficient deployment in realistic industrial scenarios
Due to the complex attention mechanisms and model design, most existing vision
Transformers (ViTs) can not perform as efficiently as convolutional neural networks (CNNs) …
Transformers (ViTs) can not perform as efficiently as convolutional neural networks (CNNs) …
Swin3d: A pretrained transformer backbone for 3d indoor scene understanding
The use of pretrained backbones with fine-tuning has been successful for 2D vision and
natural language processing tasks, showing advantages over task-specific networks. In this …
natural language processing tasks, showing advantages over task-specific networks. In this …
Elasticvit: Conflict-aware supernet training for deploying fast vision transformer on diverse mobile devices
Abstract Neural Architecture Search (NAS) has shown promising performance in the
automatic design of vision transformers (ViT) exceeding 1G FLOPs. However, designing …
automatic design of vision transformers (ViT) exceeding 1G FLOPs. However, designing …
A cnn-transformer hybrid model based on cswin transformer for uav image object detection
W Lu, C Lan, C Niu, W Liu, L Lyu… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
The object detection of unmanned aerial vehicle (UAV) images has widespread applications
in numerous fields; however, the complex background, diverse scales, and uneven …
in numerous fields; however, the complex background, diverse scales, and uneven …
Light-YOLOv5: A lightweight algorithm for improved YOLOv5 in complex fire scenarios
H Xu, B Li, F Zhong - Applied Sciences, 2022 - mdpi.com
Fire-detection technology is of great importance for successful fire-prevention measures.
Image-based fire detection is one effective method. At present, object-detection algorithms …
Image-based fire detection is one effective method. At present, object-detection algorithms …
SDBAD-Net: A spatial dual-branch attention dehazing network based on meta-former paradigm
Image dehazing is an emblematical low-level vision task that aims at restoring haze-free
images from haze images. Recently, some methods adopts deep learning techniques to …
images from haze images. Recently, some methods adopts deep learning techniques to …
TRT-ViT: TensorRT-oriented vision transformer
We revisit the existing excellent Transformers from the perspective of practical application.
Most of them are not even as efficient as the basic ResNets series and deviate from the …
Most of them are not even as efficient as the basic ResNets series and deviate from the …