Image and Video Technology
11th Pacific-Rim Symposium, PSIVT 2023, Auckland, New Zealand, November 22–24, 2023, Proceedings
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40 Result(s)
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Wei Qi Yan
Computer Science
English
Multimedia Information Systems
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Article
Moving vehicle tracking and scene understanding: A hybrid approach
In this paper, we present a novel deep learning method for detecting and tracking vehicles within the context of autonomous driving, particularly focusing on scenarios related to vehicle failures. Ensuring the...
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Article
Open AccessFruit ripeness identification using YOLOv8 model
Deep learning-based visual object detection is a fundamental aspect of computer vision. These models not only locate and classify multiple objects within an image, but they also identify bounding boxes. The fo...
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Article
Open AccessPose estimation for swimmers in video surveillance
Traditional models for pose estimation in video surveillance are based on graph structures, in this paper, we propose a method that breaks the limitation of template matching within a range of pose changes to ...
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Article
Open AccessA privacy-preserving word embedding text classification model based on privacy boundary constructed by deep belief network
To effectively extract and classify the information from reports or documents and protect the privacy of the extracted results, we propose a privacy classification named Word Embedding Combination Privacy-pres...
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Article
Open AccessCISO: Co-iteration semi-supervised learning for visual object detection
Semi-supervised learning offers a solution to the high cost and limited availability of manually labeled samples in supervised learning. In semi-supervised visual object detection, the use of unlabeled data ca...
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Article
Open AccessNUNI-Waste: novel semi-supervised semantic segmentation waste classification with non-uniform data augmentation
Waste categorization and recycling are critical approaches for converting waste into valuable and functional materials, thereby significantly aiding in land preservation, reducing pollution, and optimizing res...
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Chapter and Conference Paper
Multiscale Kiwifruit Detection from Digital Images
In this paper, we propose an improved YOLOv8-based Kiwifruit detection method using Swin Transformer, aiming to address challenges posed by significant scale variation and inaccuracies in multiscale object det...
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Chapter and Conference Paper
Computational Analysis of Table Tennis Matches from Real-Time Videos Using Deep Learning
In this paper, utilizing a multiscale training dataset, YOLOv8 demonstrates rapid inference capabilities and exceptional accuracy in detecting visual objects, particularly smaller ones. This outperforms transf...
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Chapter and Conference Paper
A High-Accuracy Deformable Model for Human Face Mask Detection
Human face mask detection leverages computer vision technology to discern whether individuals in images or videos are wearing masks. Ensuring proper mask usage is crucial in settings such as hospital operating...
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Chapter and Conference Paper
Enhancement of Human Face Mask Detection Performance by Using Ensemble Learning Models
Given the prevalence of worldwide pandemics, the need of adhering to appropriate mask use becomes more paramount. Therefore, the importance of develo** a human face mask detection model that is both efficien...
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Book and Conference Proceedings
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Article
Open AccessApple ripeness identification from digital images using transformers
We describe a non-destructive test of apple ripeness using digital images of multiple types of apples. In this paper, fruit images are treated as data samples, artificial intelligence models are employed to im...
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Article
Open AccessSign language recognition from digital videos using feature pyramid network with detection transformer
Sign language recognition is one of the fundamental ways to assist deaf people to communicate with others. An accurate vision-based sign language recognition system using deep learning is a fundamental goal fo...
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Article
An ensemble framework of deep neural networks for colorectal polyp classification
Colorectal cancer (CRC) is caused by malignant polyps which must be resected and examined for accurate classification. Biopsy, the manual workflow of polyp classification is time-intensive task and requires an...
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Chapter and Conference Paper
Traffic Sign Recognition from Digital Images by Using Deep Learning
Traffic signs are essentially needed to obey the traffic rules. Once a driver ignores the signs, especially those critical signs, due to the complexity of actual traffic scenes or the influence of inclement we...
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Chapter and Conference Paper
Depth Estimation of Traffic Scenes from Image Sequence Using Deep Learning
Autonomous cars can accurately perceive the deployment of traffic scenes and the distance between visual objects in the scenarios through understanding the depth. Therefore, the depth estimation of scenes is a...
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Chapter and Conference Paper
Waste Classification from Digital Images Using ConvNeXt
In this paper, ConvNeXt is selected as a model for waste classification from digital images. ConvNeXt is a CNN-based backbone network that has been proposed to further improve the performance of models for vis...
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Chapter and Conference Paper
A Method for Face Image Inpainting Based on Autoencoder and Generative Adversarial Network
Face image inpainting has great value in the fields of computer vision and digital image processing. In this paper, we propose a face image inpainting method based on autoencoder and Generative Adversarial Net...
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Article
Open AccessA hybrid CTC+Attention model based on end-to-end framework for multilingual speech recognition
Speech recognition is an important field in natural language processing. In this paper, the end-to-end framework for speech recognition with multilingual datasets is proposed. The end-to-end methods do not req...
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Article
Open AccessColorizing Grayscale CT images of human lungs using deep learning methods
Image colorization refers to computer-aided rendering technology which transfers colors from a reference color image to grayscale images or video frames. Deep learning elevated notably in the field of image co...
