International Journal of Applied Pattern Recognition

Scope & Guideline

Empowering research at the intersection of technology and insight.

Introduction

Welcome to the International Journal of Applied Pattern Recognition information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of International Journal of Applied Pattern Recognition, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN2049-887x
PublisherINDERSCIENCE ENTERPRISES LTD
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationINT J APPL PATTERN R / Int. J. Appl. Pattern Recognit.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressWORLD TRADE CENTER BLDG, 29 ROUTE DE PRE-BOIS, CASE POSTALE 856, CH-1215 GENEVA, SWITZERLAND

Aims and Scopes

The International Journal of Applied Pattern Recognition focuses on the development and application of pattern recognition techniques across various domains. The journal emphasizes methodologies that integrate machine learning, neural networks, and image processing to address real-world problems.
  1. Application of Machine Learning Techniques:
    The journal frequently publishes research that utilizes machine learning algorithms, particularly in the fields of healthcare, automotive safety, and character recognition, showcasing the versatility of these methods in practical applications.
  2. Image Processing and Analysis:
    A significant portion of the journal's content revolves around image processing techniques, including contour analysis and feature extraction, which are essential for tasks such as facial recognition and medical imaging.
  3. Health Informatics and Diagnostics:
    There is a strong emphasis on the application of pattern recognition in healthcare, especially in early diagnosis and disease management, indicating a core area of research that merges technology with medical science.
  4. Character Recognition and Verification:
    The journal also explores advancements in character recognition technologies, both for handwritten and typewritten text, which is crucial for digital document processing and automated systems.
  5. Survey and Review Articles:
    The inclusion of comprehensive surveys and literature reviews highlights the journal's commitment to synthesizing existing knowledge in the field, aiding researchers and practitioners in identifying trends and gaps.
Recent publications in the International Journal of Applied Pattern Recognition reveal emerging themes and trends that reflect the evolving landscape of pattern recognition and its applications. These trends are crucial for guiding future research directions.
  1. Deep Learning for Medical Applications:
    There is an increasing trend towards the application of deep learning methodologies in medical diagnostics, particularly in analyzing MRI scans and ECG signals, highlighting the importance of AI in health management.
  2. Automated Systems for Real-Time Analysis:
    Emerging research on real-time applications, such as detecting phone usage while driving, indicates a growing interest in integrating pattern recognition with automated systems for enhancing safety and efficiency.
  3. Interdisciplinary Approaches:
    Research that crosses traditional boundaries, such as the application of pattern recognition in diverse fields like insurance fraud detection, suggests a trend towards interdisciplinary studies that leverage pattern recognition in various sectors.
  4. Advanced Feature Extraction Techniques:
    There is a notable rise in the exploration of innovative feature extraction methods, as evidenced by surveys on writer identification, which underscores the need for more sophisticated techniques in pattern recognition.
  5. Emotion and Sentiment Analysis:
    The trend towards using pattern recognition for emotion classification indicates a growing interest in understanding human emotions through technology, which has significant implications for fields such as marketing and user experience.

Declining or Waning

While the journal maintains a robust focus on several core areas, certain themes have shown a decline in prominence over recent publications. This may reflect shifts in research priorities or emerging technologies.
  1. Traditional Pattern Recognition Techniques:
    Research focusing on conventional pattern recognition methods appears to be waning, as the field increasingly shifts towards more advanced machine learning and deep learning approaches.
  2. Basic Image Processing without Advanced Algorithms:
    There is a noticeable decline in studies that rely solely on basic image processing techniques without the integration of sophisticated algorithms, suggesting a movement towards more complex methodologies.
  3. General Surveys without Specific Applications:
    While surveys are still published, there seems to be less focus on general surveys that do not target specific applications, indicating a trend towards more applied and targeted research.

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