One-class defect detection has proven to be an effective technique. However, the performance of complex models is often limited by existing data augmentation methods. To address this issue, this paper proposes a novel...
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ISBN:
(纸本)9789819708109;9789819708116
One-class defect detection has proven to be an effective technique. However, the performance of complex models is often limited by existing data augmentation methods. To address this issue, this paper proposes a novel data augmentation method based on a denoising diffusion probability model. This approach generates high-quality image samples using partial noise diffusion, eliminating the need for extensive training on large-scale datasets. Experimental results demonstrate that the proposed method outperforms current methods in one-class defect detection tasks. The proposed method offers a new perspective on data augmentation and demonstrates its potential to tackle challenging computer vision problems.
This paper introduces an intelligent delta robot system enhanced with imageprocessing to optimize Pick & Place operations in Agricultural Produce Centers (APCs). Facing a critical demand for mechanization in agri...
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ISBN:
(纸本)9798331540845;9789887581598
This paper introduces an intelligent delta robot system enhanced with imageprocessing to optimize Pick & Place operations in Agricultural Produce Centers (APCs). Facing a critical demand for mechanization in agriculture due to a shrinking rural workforce, our system utilizes camera-based segmentation and depth estimation to efficiently automate the packaging of fruits and vegetables. It concentrates on essential tasks such as precise gripping and ungripping, supported by advanced camera-based visual sensors. Integrating these vision technologies with delta robot kinematics and specialized imageprocessingalgorithms allows the robot to execute highly accurate movements. Our implementation showcases significant enhancements in the efficiency and reliability of APC operations, advancing the field of agricultural robotic automation and establishing a new standard for future developments in automated food production.
The deep learning field is converging towards the use of general foundation models that can be easily adapted for diverse tasks. While this paradigm shift has become common practice within the field of natural languag...
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ISBN:
(纸本)9798350318920;9798350318937
The deep learning field is converging towards the use of general foundation models that can be easily adapted for diverse tasks. While this paradigm shift has become common practice within the field of natural language processing, progress has been slower in computer vision. In this paper we attempt to address this issue by investigating the transferability of various state-of-the-art foundation models to medical image classification tasks. Specifically, we evaluate the performance of five foundation models, namely SAM, SEEM, DINOv2, BLIP, and OPENCLIP across four well-established medical imaging datasets. We explore different training settings to fully harness the potential of these models. Our study shows mixed results. DINOv2 consistently outperforms the standard practice of imageNET pretraining. However, other foundation models failed to consistently beat this established baseline indicating limitations in their transferability to medical image classification tasks.
This article is dedicated to the study of fractal operators and the review of their application for processing medical MRI images. The Atangana-Baleanu fractial operator is discussed in detail. Four numerical approxim...
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In this paper, we present designing vibration energy harvesters based on the heart motion data achieved through imageprocessing. Energy harvesting is intended as a means to continuously produce energy by converting h...
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ISBN:
(数字)9781510671997
ISBN:
(纸本)9781510671997;9781510671980
In this paper, we present designing vibration energy harvesters based on the heart motion data achieved through imageprocessing. Energy harvesting is intended as a means to continuously produce energy by converting heart motion to electricity. This energy can be used to power pacemakers. Currently, pacemakers are powered by non-rechargeable batteries that run out in about 10 years. The pacemakers need to be surgically replaced when the batteries run out. Using energy harvesters could pave the way for permanent pacemakers that do not require periodic surgical replacement. We have developed low-frequency energy harvesting designs that have small size and at the same time can be tuned to the heart motion frequencies. One important aspect of the design process is having a reasonable estimate of the heart motion. We use imageprocessing and specifically optical flow tracking techniques to track the motion of individual points in Echo, MRI, and ultrasonic images. We experimentally test the developed harvesters to examine their power generation.
The efficiency of diagnostic processes is paramount in healthcare, particularly for breast cancer detection and treatment. This research explores the queuing dynamics within the breast cancer imaging process, emphasiz...
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作者：
Podbucki, KacperMarciniak, TomaszPoznan University of Technology
Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawla II 24 Poznań60-965 Poland
Measuring luminous intensity using electronic sensors requires their precise positioning. In the case of mobile measurement platforms, it is important to detect the light source and thus determine the correct directio...
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Machine vision and computer imageprocessing technologies are widely used in the metallurgical industry, especially in recognizing and analyzing defects in glass. High surfaces of planer surface and quality in the gla...
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In order to improve the segmentation accuracy of 3D point cloud model in feature ambiguous region, the unsupervised clustering algorithm based on surface fusion features combines the depth residuals with the normal de...
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Object tracking is a widely used algorithm in imageprocessing. When tracking objects on thermal images, however, issues, such as changes in size, temporary occlusion, lack of prominent features, and active thermal no...
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