Results 71 to 80 of about 8,876 (216)
Network structure of Swin-Transformer-YOLOv5.
An essential industrial application is the examination of surface flaws in hot-rolled steel strips. While automatic visual inspection tools must meet strict real-time performance criteria for inspecting hot-rolled steel strips, their capabilities are ...
Haoyue Huang (3450605) +2 more
core +1 more source
Remote Sensing in Ecology and Conservation, EarlyView.We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang +5 more
wiley +1 more source
The effect of Swin-Transformer-YOLOV5 and YOLOV5S on 6 types of defects detection.
The effect of Swin-Transformer-YOLOV5 and YOLOV5S on 6 types of defects detection.
Haoyue Huang (3450605) +2 more
core +1 more source
Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel +2 more
wiley +1 more source
Diverse features discovery transformer for pedestrian attribute recognition
, 2023 Recently, Swin Transformer has been widely explored as a general backbone for computer vision, which helps to improve the performance of vision tasks due to the ability to establish associations for long-range dependencies of different spatial locations.
Hussain, Amir +5 more
core +2 more sources
Classifying Deepfakes Using Swin Transformers
CoRR3 ...
Aprille J. Xi, Eason Chen
openaire +2 more sources
A Multi‐Sequence Adversarial Fusion U‐Net for Brain Tumor Image Segmentation
IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.In the field of brain tumor image segmentation, in order to avoid the impact of insufficient number of training samples, the method of fusing multi‐modal MRI information before segmentation is widely used. However, when fusing different modal features, existing methods only add fixed weights to the features of each modality, resulting in insufficient ...
Jie Wang, Jinglu Hu
wiley +1 more source
Few-Shot Image Classification Algorithm of Graph Neural Network Based on Swin Transformer
In fewshot image classification tasks, capturing remote semantic information in feature extraction modules based on convolutional neural network and single measure of edgefeature similarity are challenging.
Zhang, W, Ren, J, Wang, K
core +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam +3 more
wiley +1 more source
DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu +3 more
wiley +1 more source