Deep Industrial Image Anomaly Detection: A Survey (2301.11514v5)

Abstract: The recent rapid development of deep learning has laid a milestone in industrial Image Anomaly Detection (IAD). In this paper, we provide a comprehensive review of deep learning-based image anomaly detection techniques, from the perspectives of neural network architectures, levels of supervision, loss functions, metrics and datasets. In addition, we extract the new setting from industrial manufacturing and review the current IAD approaches under our proposed our new setting. Moreover, we highlight several opening challenges for image anomaly detection. The merits and downsides of representative network architectures under varying supervision are discussed. Finally, we summarize the research findings and point out future research directions. More resources are available at https://github.com/M-3LAB/awesome-industrial-anomaly-detection.

An Overview of a Placeholder Document

The document provided is a LaTeX template for writing preprint versions of academic papers, specifically utilizing the elsarticle class. This template is commonly used for drafting papers that are submitted to journals published by Elsevier, a significant academic publisher. The template, in its current state, does not contain specific research content but rather focuses on formatting and structure.

Structure and Components

The document uses the preprint, review, and 12pt options within the class, which are indicative of its intended use before formal publication. This configuration typically aids in facilitating the peer review process by ensuring that the manuscript is easily readable and contains ample space for reviewers' comments.

The primary components involved in this document are:

• Bibliography Style and Management: The template sets the bibliography style using plain and manages references via a reference.bib file indicated by \bibliography{reference.bib}. These components are essential in academic writing as they ensure proper citation formatting and management of the literature referenced in the paper.
• Document Structure: The document encompasses basic LaTeX commands to initiate the paper's structure and layout aspects but lacks detailed sections such as abstract, introduction, methodology, results, and discussion, which would characterize a typical research paper.

Implications for Future Research Writing

The implications of using such a LaTeX template are primarily practical, focusing on standardization and efficiency in academic writing. Templates like this one streamline the drafting process, allowing researchers to concentrate on the substance of their work rather than the intricacies of formatting. Furthermore, ensuring adherence to journal-specific formatting guidelines can significantly enhance the likelihood of successful manuscript submission and acceptance.

Speculation on Future Developments

As academic publishing continues to evolve, there may be a shift towards more integrated platforms that combine traditional LaTeX capabilities with real-time collaboration features. Future templates may increasingly incorporate automated tools for checking compliance with ethical guidelines, journal standards, and even preliminary peer review assessments. These advancements would further reduce administrative burdens on researchers, enabling a stronger emphasis on innovative content development and interdisciplinary collaboration.

Conclusively, while this document serves a foundational purpose, the ongoing evolution in academic tools and platforms is poised to refine and enhance the processes surrounding academic manuscript preparation and submission.