International Journal of Neural Networks and Deep Learning (IJNNDL)

The International Journal of Neural Networks and Deep Learning (IJNNDL) aims to advance the field of neural networks and deep learning by publishing original, high-quality research that drives innovation and deepens understanding. The journal seeks to be a premier platform for disseminating cutting-edge research and developments in neural network technologies and their applications. It is dedicated to fostering interdisciplinary collaboration and providing researchers, practitioners, and academics with valuable insights and practical solutions in the realm of deep learning. SCOPE International Journal of Neural Networks and Deep Learning (IJNNDL) encompasses a broad range of topics related to neural networks and deep learning. It focuses on publishing comprehensive research articles that address both foundational theories and applied techniques. The scope of the journal includes but is not limited to the exploration of novel neural network architectures, the development of innovative algorithms, and the application of deep learning technologies to real-world problems. The journal encourages submissions that offer significant contributions to the field, including advances in model design, optimization methods, performance evaluation, and the deployment of deep learning systems. IJNNDL is dedicated to highlighting research that bridges the gap between theoretical advancements and practical applications, thereby supporting the progression of the field. It welcomes contributions from researchers, practitioners, and academics that offer new insights, challenge existing paradigms, and propose solutions to contemporary challenges in neural networks and deep learning

International Journal of Neural Networks and Deep Learning (IJNNDL) is :-

• International, Peer-Reviewed, Open Access, Refereed, Neural Network Architectures, Deep Learning Algorithms and Models, Applications and Use Cases, Theoretical Foundations, Implementation and Performance, Emerging Trends and Innovations, Software Libraries and Platforms, Model Development and Experimentation Tools , Online , Monthly Journal

• UGC Approved, ISSN Approved: P-ISSN E-ISSN: 3851-5221, Established: 2024, Impact Factor: 2.80
• Provides Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE