Automatic Defects Recognition of Lap Joint of Unequal Thickness Based on X-Ray Image Processing DOI Open Access
Dazhao Chi, Ziming Wang, Haichun Liu

et al.

Materials, Journal Year: 2024, Volume and Issue: 17(22), P. 5463 - 5463

Published: Nov. 8, 2024

It is difficult to automatically recognize defects using digital image processing methods in X-ray radiographs of lap joints made from plates unequal thickness. The continuous change the wall thickness joint workpiece causes very different gray levels an background image. Furthermore, due shape and fixturing workpiece, distribution weld seam radiograph not vertical which results angle between direction. This makes automatic defect detection localization difficult. In this paper, a method correction based on invariant moments presented solve problem. addition, novel removal introduced reduce difficulty recognition caused by variations grayscale. At same time, combining noise suppression, segmentation, mathematical morphology adopted. show that proposed can effectively gas pores welded thickness, making it suitable for detection.

Language: Английский

Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications DOI Open Access

Răzvan Onciul,

Cătălina-Ioana Tătaru,

Adrian Dumitru

et al.

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(2), P. 550 - 550

Published: Jan. 16, 2025

The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding the brain, unlocking new possibilities in research, diagnosis, therapy. This review explores how AI’s cutting-edge algorithms—ranging from deep learning to neuromorphic computing—are revolutionizing by enabling analysis complex neural datasets, neuroimaging electrophysiology genomic profiling. These advancements are transforming early detection neurological disorders, enhancing brain–computer interfaces, driving personalized medicine, paving way for more precise adaptive treatments. Beyond applications, itself has inspired AI innovations, with architectures brain-like processes shaping advances algorithms explainable models. bidirectional exchange fueled breakthroughs such as dynamic connectivity mapping, real-time decoding, closed-loop systems that adaptively respond states. However, challenges persist, including issues data integration, ethical considerations, “black-box” nature many systems, underscoring need transparent, equitable, interdisciplinary approaches. By synthesizing latest identifying future opportunities, this charts a path forward integration neuroscience. From harnessing multimodal cognitive augmentation, fusion these fields not just brain science, it reimagining human potential. partnership promises where mysteries unlocked, offering unprecedented healthcare, technology, beyond.

Language: Английский

Citations

5
Multi-wavelength spectral reconstruction with localized speckle pattern DOI
Junrui Liang, Jun Li, Junhong He

et al.

Optics Communications, Journal Year: 2024, Volume and Issue: 575, P. 131266 - 131266

Published: Nov. 1, 2024

Language: Английский

Citations

0
Multi-Domain Data Integration for Plasma Diagnostics in Semiconductor Manufacturing Using Tri-CycleGAN DOI Creative Commons
Minji Kang, Sung Kyu Jang,

J.H. Kim

et al.

Journal of Sensor and Actuator Networks, Journal Year: 2024, Volume and Issue: 13(6), P. 75 - 75

Published: Nov. 4, 2024

The precise monitoring of chemical reactions in plasma-based processes is crucial for advanced semiconductor manufacturing. This study integrates three diagnostic techniques—Optical Emission Spectroscopy (OES), Quadrupole Mass Spectrometry (QMS), and Time-of-Flight (ToF-MS)—into a reactive ion etcher (RIE) system to analyze CF4-based plasma. To synchronize integrate data from these different domains, we developed Tri-CycleGAN model that utilizes interconnected CycleGANs bi-directional transformation between OES, QMS, ToF-MS. configuration enables accurate mapping across effectively compensating the blind spots individual techniques. incorporates self-attention mechanisms address temporal misalignments direct loss function preserve fine-grained features, further enhancing accuracy. Experimental results show achieves high consistency reconstructing plasma measurement under various conditions. model’s ability fuse multi-domain offers robust solution monitoring, potentially improving precision, yield, process control work lays foundation future applications machine learning-based integration complex environments.

Language: Английский

Citations

0
Automatic Defects Recognition of Lap Joint of Unequal Thickness Based on X-Ray Image Processing DOI Open Access
Dazhao Chi, Ziming Wang, Haichun Liu

et al.

Materials, Journal Year: 2024, Volume and Issue: 17(22), P. 5463 - 5463

Published: Nov. 8, 2024

It is difficult to automatically recognize defects using digital image processing methods in X-ray radiographs of lap joints made from plates unequal thickness. The continuous change the wall thickness joint workpiece causes very different gray levels an background image. Furthermore, due shape and fixturing workpiece, distribution weld seam radiograph not vertical which results angle between direction. This makes automatic defect detection localization difficult. In this paper, a method correction based on invariant moments presented solve problem. addition, novel removal introduced reduce difficulty recognition caused by variations grayscale. At same time, combining noise suppression, segmentation, mathematical morphology adopted. show that proposed can effectively gas pores welded thickness, making it suitable for detection.

Language: Английский

Citations

0