paper-with-me

홈 › Papers

VizInspect Pro -- Automated Optical Inspection (AOI) solution

2022-05-26 · Faraz Waseem, Sanjit Menon, Haotian Xu, Debashis Mondal

Traditional vision based Automated Optical Inspection (referred to as AOI in paper) systems present multiple challenges in factory settings including inability to scale across multiple product lines, requirement of vendor programming expertise, little tolerance to variations and lack of cloud connectivity for aggregated insights. The lack of flexibility in these systems presents a unique opportunity for a deep learning based AOI system specifically for factory automation. The proposed solution, VizInspect pro is a generic computer vision based AOI solution built on top of Leo - An edge AI platform. Innovative features that overcome challenges of traditional vision systems include deep learning based image analysis which combines the power of self-learning with high speed and accuracy, an intuitive user interface to configure inspection profiles in minutes without ML or vision expertise and the ability to solve complex inspection challenges while being tolerant to deviations and unpredictable defects. This solution has been validated by multiple external enterprise customers with confirmed value propositions. In this paper we show you how this solution and platform solved problems around model development, deployment, scaling multiple inferences and visualizations.

📄 PDF Abstract BibTeX arXiv:2205.13095

Code (0)

등록된 구현이 없습니다.

Tasks

Self-Learning

Methods 이 논문이 사용한 방법론

SPEED The monocular depth estimation (MDE) is the task of estimating depth from a single frame. This information is an essential knowledge in many computer vision tasks such as scene…
Self-Learning 설명 없음

Similar Papers 제목 키워드 기반

Physical Annotation for Automated Optical Inspection: A Concept for In-Situ, Pointer-Based Trainingdata Generation

2025-06-05 · Oliver Krumpek, Oliver Heimann, Jörg Krüger

This paper introduces a novel physical annotation system designed to generate training data for automated optical inspection. The system uses pointer-based in-situ interaction to transfer the valuable expertise of traine…

FPIC: A Novel Semantic Dataset for Optical PCB Assurance

2022-02-17 · Nathan Jessurun, Olivia P. Dizon-Paradis, Jacob Harrison, Shajib Ghosh 외

Outsourced printed circuit board (PCB) fabrication necessitates increased hardware assurance capabilities. Several assurance techniques based on automated optical inspection (AOI) have been proposed that leverage PCB ima…

2D Tiny Object Detection

Design and Development of a Robust Tolerance Optimisation Framework for Automated Optical Inspection in Semiconductor Manufacturing

2025-05-06 · Shruthi Kogileru, Mark McBride, Yaxin Bi, Kok Yew Ng

Automated Optical Inspection (AOI) is widely used across various industries, including surface mount technology in semiconductor manufacturing. One of the key challenges in AOI is optimising inspection tolerances. Tradit…

Efficient Neural Network Compression via Transfer Learning for Industrial Optical Inspection

2018-10-20 · Seunghyeon Kim, Yung-Kyun Noh, Frank C. Park

In this paper, we investigate learning the deep neural networks for automated optical inspection in industrial manufacturing. Our preliminary result has shown the stunning performance improvement by transfer learning fro…

Neural Network CompressionTransfer Learning

Technical Report: Automated Optical Inspection of Surgical Instruments

2026-03-06 · Zunaira Shafqat, Atif Aftab Ahmed Jilani, Qurrat Ul Ain arxiv

In the dynamic landscape of modern healthcare, maintaining the highest standards in surgical instruments is critical for clinical success. This report explores the diverse realm of surgical instruments and their associat…