International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 3 (May-June 2025) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

The Evolution of Computer Vision: Trends, Challenges, and the Role of Hybrid CNN-Transformer Models in Enhancing Interpretability and Training Dynamics

Author(s) Ms. vaidehi siddheshwar kokare, Ms. vedanti sandiprao kavitkar, Ms. sonia Munnalal Jangid
Country India
Abstract The goal of computer vision, a branch of artificial intelligence (AI), is to enable machines to process and interpret visual data. From manual feature extraction in the past to advanced deep learning models like VisionTransformers (ViTs) and ConvolutionalNeuralNetworks (CNNs), computer vision has evolved throughout time. Despite their success, these models face challenges related to interpretability, training complexity, and computational load. This research explores the integration of CNNs and ViTs into hybrid architectures, aiming to enhance model transparency, efficiency, and performance in real-world applications.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-04
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.42100
Short DOI https://doi.org/g9hscx

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