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Global Journal of Engineering and Technology Advances
International Peer reviewed Engineering Journal || Crossref DOI || Impact Factor 8.6 || ISSN: 2582-5003

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Research & review articles are invited for publication in September 2026 (Vol. 28, Issue 3) || Submission: up to 28th September || Editorial decision: within 48 hrs.

🧠 Deep Learning Journal

International Peer-Reviewed Open Access Deep Learning Journal with Fast Publishing, Crossref DOI at No Additional Cost, Free Certificate of Publication and Low Publication Charges

Global Journal of Engineering and Technology Advances (GJETA) is an International Peer-Reviewed Open Access Deep Learning Journal publishing high-quality Original Research Articles and Review Articles.

GJETA offers Fast Publishing, independent Peer Review, Crossref DOI assignment at no additional cost, a Free Certificate of Publication for every accepted article, worldwide Open Access visibility, and Low Publication Charges of only USD 35 for international authors and INR 2100 for Indian authors.

📄 Submit Your Manuscript 📋 Author Guidelines 💰 Publication Charges 

Deep Learning Journal | Peer-Reviewed Open Access Journal | GJETA

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  • Deep Learning Journal | Peer-Reviewed Open Access Journal | GJETA

⭐ Why Choose GJETA as Your Deep Learning Journal?

Selecting the right Deep Learning Journal is essential for researchers seeking international visibility, scientific credibility, and real-world technological impact. A high-quality journal should provide independent Peer Review, ethical editorial practices, Open Access publishing, worldwide discoverability, and efficient editorial processing. Global Journal of Engineering and Technology Advances (GJETA) supports multidisciplinary research spanning deep learning, artificial intelligence, machine learning, computer vision, natural language processing, robotics, autonomous systems, healthcare AI, business analytics, and intelligent engineering applications.

Journal HighlightsBenefits for Authors
🌍 Journal TypeInternational Peer-Reviewed Open Access Deep Learning Journal
👨‍⚖️ Peer ReviewIndependent expert review process
⚡ PublishingFast Publishing with efficient editorial workflow
🔗 Crossref DOIAssigned to every accepted article at no additional cost
📜 Publication CertificateFree Certificate of Publication for every accepted article
🌐 Open AccessWorldwide visibility and unrestricted accessibility
💰 Publication ChargesOnly USD 35 / INR 2100
📈 Research VisibilityGreater international discoverability and academic recognition

🚀 Publish Your Deep Learning Research Internationally

Whether your research focuses on Deep Neural Networks, CNN, RNN, Transformers, Large Language Models, Computer Vision, Natural Language Processing, Speech Recognition, Generative AI, Explainable AI, Reinforcement Learning, Autonomous Systems, Multimodal Learning, or Intelligent Robotics, Global Journal of Engineering and Technology Advances (GJETA) provides an International Peer-Reviewed Open Access Deep Learning Journal offering Fast Publishing, Crossref DOI at no additional cost, a Free Certificate of Publication, and Low Publication Charges of only USD 35 / INR 2100.

📄 Submit Your Deep Learning Paper →


🧠 Scope of the Deep Learning Journal

The Deep Learning Journal publishes original research covering deep neural networks, convolutional neural networks, recurrent neural networks, transformer architectures, large language models, generative AI, computer vision, natural language processing, speech and audio processing, multimodal AI, reinforcement learning, autonomous systems, explainable AI, edge AI, federated learning, intelligent robotics, healthcare AI, industrial AI, and advanced deep learning applications. As an Open Access Deep Learning Journal, GJETA welcomes interdisciplinary research integrating deep learning with engineering, computer science, healthcare, manufacturing, transportation, finance, agriculture, cybersecurity, and emerging intelligent technologies.

Every manuscript submitted to this Peer-Reviewed Deep Learning Journal is evaluated for originality, algorithmic innovation, experimental validation, computational performance, engineering significance, scientific contribution, and practical applicability. Researchers from universities, research laboratories, technology companies, AI startups, healthcare organisations, manufacturing industries, and government institutions are encouraged to publish their latest deep learning innovations.


⚙️ Major Research Areas

Research AreaExample Topics
Deep Neural NetworksDNN, CNN, RNN, Transformer Architectures
Large Language ModelsLLMs, Generative AI, Foundation Models
Computer VisionObject Detection, Image Recognition, Medical Imaging
Natural Language ProcessingLanguage Models, Chatbots, Text Understanding
Speech & Audio AISpeech Recognition, Audio Processing, Voice Intelligence
Reinforcement LearningAutonomous Systems, Intelligent Agents
Explainable AIInterpretable Deep Learning Models
Healthcare & Industrial AIMedical Diagnosis, Predictive Maintenance, Smart Manufacturing
Edge AI & Federated LearningDistributed Intelligence and Privacy-Preserving AI
Multimodal AIVision-Language Models, Cross-Modal Learning

🎯 Why Publish Deep Learning Research in GJETA?

Publishing in a reputable Deep Learning Journal enables researchers to share innovative algorithms, intelligent systems, computational models, and practical artificial intelligence applications with an international scientific community. High-quality publication supports academic recognition, industrial collaboration, technology transfer, and wider adoption of advanced deep learning methodologies across multiple engineering and scientific disciplines.

As an International Peer-Reviewed Open Access Deep Learning Journal, Global Journal of Engineering and Technology Advances (GJETA) provides an ethical publication platform for researchers working in artificial intelligence, machine learning, computer vision, robotics, natural language processing, healthcare AI, industrial automation, autonomous systems, and emerging intelligent technologies.

Publishing BenefitValue for Authors
🌍 Worldwide Open AccessResearch becomes freely accessible to researchers, universities, industries, and technology professionals worldwide.
👨‍⚖️ Independent Peer ReviewEach manuscript undergoes rigorous scientific and technical evaluation.
⚡ Fast PublishingEfficient editorial processing ensures timely publication while maintaining publication quality.
🔗 Crossref DOIEvery accepted article receives a permanent Crossref DOI at no additional cost.
📜 Free Publication CertificateA complimentary publication certificate is provided for every published article.
📈 Global Research VisibilityOpen Access publication improves discoverability, readership, and citation potential.
🤝 Multidisciplinary ImpactSuitable for research connecting AI with engineering, healthcare, manufacturing, business, finance, agriculture, and environmental sciences.
💰 Affordable PublicationTransparent publication charges of USD 35 for international authors and INR 2100 for Indian authors.

🚀 Publish High-Impact Deep Learning Research

Whether your work focuses on computer vision, large language models, intelligent robotics, reinforcement learning, explainable AI, speech recognition, generative AI, healthcare AI, or industrial automation, Global Journal of Engineering and Technology Advances (GJETA) provides an International Peer-Reviewed Open Access Deep Learning Journal offering Fast Publishing, Crossref DOI at no additional cost, a Free Certificate of Publication, and affordable publication charges of USD 35 / INR 2100.

📄 Submit Your Deep Learning Research →


👨‍🔬 Who Can Publish in the Deep Learning Journal?

The Deep Learning Journal welcomes original and interdisciplinary contributions from undergraduate and postgraduate students, doctoral researchers, faculty members, artificial intelligence scientists, data scientists, software engineers, robotics researchers, computer vision specialists, healthcare AI researchers, industrial R&D professionals, and multidisciplinary research teams. Manuscripts are evaluated based on originality, methodological quality, engineering significance, computational performance, scientific contribution, and practical applicability.

Author CategorySuitable Contributions
🎓 StudentsResearch projects, intelligent applications, algorithm development, and AI innovations.
👨‍🎓 Research ScholarsAdvanced deep learning architectures, novel AI models, and interdisciplinary research.
👩‍🏫 Faculty MembersIndependent, funded, collaborative, and applied artificial intelligence research.
💻 AI & Software EngineersReal-world AI applications, intelligent systems, optimization, and deployment studies.
🏭 Industry ResearchersIndustrial AI, predictive analytics, smart manufacturing, healthcare AI, and automation.
🤝 Multidisciplinary TeamsResearch integrating deep learning with engineering, healthcare, agriculture, business, and environmental sciences.

📄 Types of Articles Published

The Deep Learning Journal publishes scholarly manuscripts presenting innovative algorithms, intelligent computational models, engineering applications, industrial case studies, AI frameworks, optimization methods, software implementations, and systematic reviews covering recent developments in deep learning and artificial intelligence.

Article TypeDescription
📘 Original Research ArticlesNovel deep learning models, algorithms, architectures, experimental studies, and engineering applications.
📗 Review ArticlesComprehensive reviews of deep learning technologies, trends, methodologies, and future research directions.
📙 Short CommunicationsBrief reports presenting innovative AI concepts, experimental findings, or emerging technologies.
📕 Technical NotesImplementation methods, optimization techniques, datasets, frameworks, software tools, and engineering solutions.

🌍 Publish Innovative Artificial Intelligence and Deep Learning Research

Researchers developing intelligent algorithms, advanced neural networks, computer vision systems, natural language processing models, large language models, reinforcement learning frameworks, healthcare AI, industrial AI, autonomous systems, and next-generation intelligent technologies are invited to publish with Global Journal of Engineering and Technology Advances (GJETA). Authors benefit from independent Peer Review, worldwide Open Access visibility, Fast Publishing, Crossref DOI assignment at no additional cost, a Free Certificate of Publication, and affordable publication charges of USD 35 / INR 2100.

🚀 Submit Your Deep Learning Manuscript →


🏆 Why Researchers Choose GJETA for Deep Learning Publication

Researchers selecting a Deep Learning Journal seek a publication platform that combines scientific quality, ethical publishing, rapid editorial processing, international visibility, and multidisciplinary impact. Global Journal of Engineering and Technology Advances (GJETA) provides these advantages while supporting research that connects artificial intelligence with engineering, healthcare, manufacturing, robotics, cybersecurity, business analytics, environmental monitoring, and intelligent automation.

  • ✅ International Peer-Reviewed Open Access Deep Learning Journal.
  • ✅ Independent editorial screening and expert Peer Review.
  • ✅ Fast Publishing with transparent editorial workflow.
  • ✅ Crossref DOI assigned to every accepted article at no additional cost.
  • ✅ Free Certificate of Publication for every published article.
  • ✅ Worldwide Open Access visibility.
  • ✅ Low Publication Charges of USD 35 / INR 2100.
  • ✅ Suitable for researchers from academia, industry, startups, and research laboratories.
  • ✅ Supports interdisciplinary artificial intelligence and engineering research.
  • ✅ Publishes Original Research Articles, Review Articles, Short Communications, and Technical Notes.

🌐 Related Deep Learning Research Areas Covered by GJETA Journal

This Deep Learning page is one of the specialized research areas covered by the Global Journal of Engineering and Technology Advances (GJETA). Deep learning research naturally integrates with artificial intelligence, machine learning, computer science engineering, robotics and automation, information technology, electronics engineering, communication engineering, business analytics, industrial engineering, and intelligent decision systems. Researchers are encouraged to explore these related research areas for multidisciplinary collaboration and publication opportunities.

  • 🤖 Artificial Intelligence and Data Science
  • 🧠 Machine Learning
  • ⚙️ Robotics and Automation Engineering
  • 💻 Computer Science Engineering
  • 🌐 Information Technology
  • 📡 Electronics Engineering
  • 📶 Communication Engineering
  • 🔋 Electrical Engineering
  • 📊 Business Analytics and Decision Sciences
  • 📈 Management Science and Operations Research
  • 🏭 Industrial Engineering
  • 🧬 Nanotechnology Engineering

Explore our comprehensive Engineering Research Journal to discover all engineering and technology research areas covered by Global Journal of Engineering and Technology Advances (GJETA), identify the most suitable subject area for your manuscript, and explore multidisciplinary publication opportunities.


📚 Helpful Resources for Authors

  • 📋 Author Guidelines
  • 📄 Online Manuscript Submission
  • 💰 Article Processing Charges
  • 👨‍⚖️ Peer Review Process
  • 🌐 Open Access Policy
  • 🔗 Crossref DOI Information
  • 📜 Free Certificate of Publication
  • 📧 Contact the Editorial Office

❓ Frequently Asked Questions About Deep Learning Journal


1. What is a Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) is an International Peer-Reviewed Open Access Deep Learning Journal that publishes Original Research Articles and Review Articles covering deep neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), transformer architectures, large language models (LLMs), computer vision, natural language processing, reinforcement learning, generative AI, explainable AI, and intelligent engineering applications.


2. Which research areas are covered by the Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) welcomes research on deep neural networks, CNN, RNN, transformer models, large language models, computer vision, natural language processing, speech recognition, generative AI, reinforcement learning, explainable AI, multimodal learning, healthcare AI, industrial AI, intelligent robotics, autonomous systems, federated learning, edge AI, and advanced deep learning applications.


3. Who can publish in the Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) welcomes submissions from undergraduate and postgraduate students, research scholars, faculty members, artificial intelligence researchers, machine learning engineers, data scientists, software engineers, industry professionals, and multidisciplinary research teams developing innovative deep learning technologies.


4. What types of manuscripts are accepted by the Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) publishes Original Research Articles, Review Articles, Short Communications, and Technical Notes covering deep learning algorithms, intelligent neural network architectures, engineering applications, computational models, software frameworks, experimental studies, and interdisciplinary artificial intelligence research.


5. Why publish in the Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) offers independent Peer Review, Fast Publishing, Open Access publication, Crossref DOI assignment at no additional cost, a Free Certificate of Publication, worldwide research visibility, and affordable publication charges of only USD 35 for international authors and INR 2100 for Indian authors.


6. Does the Deep Learning Journal provide Crossref DOI for every accepted article?

Global Journal of Engineering and Technology Advances (GJETA) assigns a permanent Crossref Digital Object Identifier (DOI) to every accepted article at no additional cost, ensuring reliable citation, permanent accessibility, improved discoverability, and long-term academic visibility.


7. What are the publication charges for the Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) charges only USD 35 for international authors and INR 2100 for Indian authors. The publication fee includes editorial processing, independent Peer Review, Open Access publication, Crossref DOI assignment, online hosting, and a Free Certificate of Publication.


8. Does the Deep Learning Journal support Fast Publishing?

Global Journal of Engineering and Technology Advances (GJETA) follows an efficient editorial workflow designed to support Fast Publishing while maintaining rigorous Peer Review and high publication standards. Publication timelines depend on editorial screening, reviewer availability, manuscript revisions, acceptance, and final production.


9. Can interdisciplinary research be submitted to the Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) encourages interdisciplinary research integrating deep learning with artificial intelligence, machine learning, computer vision, robotics, healthcare, cybersecurity, manufacturing, finance, agriculture, environmental sciences, intelligent transportation, and other emerging engineering technologies.


10. How can authors submit a manuscript to the Deep Learning Journal?

Global Journal of Engineering and Technology Advances (GJETA) accepts manuscripts through its online submission system. Authors should prepare their manuscript according to the Author Guidelines and submit it via the Online Manuscript Submission page. Every submission undergoes editorial screening followed by independent Peer Review before the final publication decision.


🎯 Conclusion

A Deep Learning Journal serves as an international platform for publishing innovative research that advances artificial intelligence, intelligent automation, computational intelligence, and next-generation engineering technologies. High-quality deep learning research continues to transform healthcare, manufacturing, transportation, finance, robotics, communication systems, and numerous interdisciplinary scientific fields.

Global Journal of Engineering and Technology Advances (GJETA) is an International Peer-Reviewed Open Access Deep Learning Journal publishing high-quality Original Research Articles and Review Articles. Authors benefit from independent Peer Review, Fast Publishing, Crossref DOI at no additional cost, a Free Certificate of Publication, worldwide Open Access visibility, and affordable publication charges of USD 35 / INR 2100.

🚀 Publish Your Deep Learning Research with GJETA

Submit your Original Research Article, Review Article, Short Communication, or Technical Note to Global Journal of Engineering and Technology Advances (GJETA). Publish through an International Peer-Reviewed Open Access Deep Learning Journal offering Fast Publishing, Crossref DOI at no additional cost, a Free Certificate of Publication, and Low Publication Charges of only USD 35 / INR 2100.

📄 Submit Your Deep Learning Manuscript 


Publication Procedure at GJETA

Follow these simple steps to submit, review, and publish your engineering and technology research with Global Journal of Engineering and Technology Advances (GJETA).

📤

Submit Your Manuscript

Step 1: Submit your engineering or technology manuscript online or email it to the Editorial Office along with the required supporting documents.

Submit Manuscript Online → 

📋

Editorial Screening & Peer Review

Step 2: Every submitted manuscript undergoes initial editorial screening followed by an independent peer review conducted by qualified engineering and technology experts.

Track Manuscript Status → 

💳

Pay Article Processing Charges

Step 3: After final acceptance, authors pay the Article Processing Charges (APC) of USD 35 or INR 2100 before publication.

View Article Processing Charges → 

📄

Online Article Publication

Step 4: The accepted article is published online with Open Access access, a Crossref DOI, and an electronic publication certificate for the corresponding author.

Get Publication Certificate → 

          

 

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