Titlebook: Image and Video Technology; 11th Pacific-Rim Sym Wei Qi Yan,Minh Nguyen,Xuejun Li Conference proceedings 2024 The Editor(s) (if applicable)

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TOXIC

,Image Recognition and Threat Detection in Bags Arriving at the Airport, the help of X-ray or computed tomography machines. There is a need for an automatic system which could reduce the time of the screening process and possibly, increase the accuracy of the detections. More than that, there is a demand for developing and evaluating methodologies for learning on 3D ima

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,Local Brightness Normalization for Image Classification and Object Detection Robust to Illuminationhat contain severe illumination changes which often occur in practice. To improve the robustness of networks to illumination changes, we propose to use local brightness normalization (LBN) as pre-processing of the input images and to train the network on those normalized images. The LBN can convert

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omnibus

Multiscale Kiwifruit Detection from Digital Images,t scale variation and inaccuracies in multiscale object detection. Specifically, our approach embeds the encoder from Swin Transformer, based on its sliding-window design, into the YOLOv8 architecture to capture contextual information and global dependencies of the detected objects at multiple scale

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,A High-Accuracy Deformable Model for Human Face Mask Detection,ask usage is crucial in settings such as hospital operating rooms and flu clinics. As deep learning advances, face mask detection has emerged as a significant research area within the computer vision field. In this paper, we propose a deformable state-of-the-art (DSOTA) model based on Deformable Con

garrulous

,MobileNet-SA: Lightweight CNN with Self Attention for Sketch Classification,al. While CNNs have demonstrated remarkable success in various image-related tasks, the computational complexity of large models poses challenges in resource-constrained environments. To address this concern, we propose MobileNet-SA, a novel lightweight model that seamlessly integrates a self-attent

MUTED

,Enhancement of Human Face Mask Detection Performance by Using Ensemble Learning Models,ing a human face mask detection model that is both efficient and accurate cannot be overstated. Nevertheless, there is a need for additional enhancement in the accuracy and efficiency of face mask detection algorithms, particularly in dealing with increasingly complex scenarios. In this paper, we ma

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