Results 71 to 80 of about 206,029 (232)
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
Speech Swin-Transformer: Exploring a Hierarchical Transformer with Shifted Windows for Speech Emotion Recognition [PDF]
Swin-Transformer has demonstrated remarkable success in computer vision by leveraging its hierarchical feature representation based on Transformer. In speech signals, emotional information is distributed across different scales of speech features, e.\,g.,
Lu, Cheng +6 more
core +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
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
Cryo-electron micrograph images have various characteristics such as varying sizes, shapes, and distribution densities of individual particles, severe background noise, high levels of impurities, irregular shapes, blurred edges, and similar color to the ...
JinLing Wang (18334331) +6 more
core +1 more source
Abstract Automating bridge inspections requires more than detecting individual damage instances. It demands systems capable of describing, contextualizing, and interpreting damage in an inspection‐relevant manner. Conventional computer vision approaches, such as object detection and segmentation, primarily address visual recognition tasks and are ...
Rona Firdes Çelik +2 more
wiley +1 more source
Comparison of AR between the Swin-cryoEM model and Swin Transformer model.
Comparison of AR between the Swin-cryoEM model and Swin Transformer model.
JinLing Wang (18334331) +6 more
core +1 more source
A Multi‐Sequence Adversarial Fusion U‐Net for Brain Tumor Image Segmentation
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
Low‐contrast capillaries are often missed or fragmented by segmentation models, so we developed a shallow four‐level starU‐Net that combines star operation‐based feature extraction with dynamic snake convolution‐based multi‐view fusion for improved thin vessel continuity.
Mengwei Bai +3 more
wiley +1 more source
Advanced deepfake detection leveraging swin transformer technology [PDF]
The widespread use of deepfake technology in recent years has made it extremely difficult to differentiate between real and fake images, usually AI-generated images.
Gourisaria, Mahendra Kumar +3 more
core +1 more source

