Published Online:August 2024
Product Name:The IUP Journal of Operations Management
Product Type:Article
Product Code:
Author Name:Sandeep Bhattacharjee
Availability:YES
Subject/Domain:Management
Download Format:PDF
Pages:12
Retail warehouses, also known as distribution centers or fulfillment centers, are facilities used by retailers for storing and distributing goods to their stores or directly to customers. These warehouses play a crucial role in the supply chain, ensuring that products are available when and where they are needed. This paper explores, through a literature review, the significant role played by deep learning in modern retail warehouses, primarily in optimizing various aspects of warehouse operations. Some real-life case studies have also been examined to understand the benefits, prospects and challenges. The paper will be of use for academicians, industrialists and policymakers as it provides insights into real-time implementation of deep learning applications.
Deep learning is rapidly being used in modern retail warehouses to improve many elements of warehouse operations, maximize efficiency, and boost overall performance. The use of deep learning techniques in modern retail warehouses has sparked widespread interest due to its potential to improve efficiency and optimize different areas of warehouse operations. This paper provides a review of current research on the use of deep learning in retail warehousing, with an emphasis on key aspects such as inventory management, warehouse automation, quality control, and customer experience. Intelligent computer applications are currently used in a variety of fields, including retail businesses. Customer behavior analysis is becoming increasingly important for both customers and companies. In this context, the unique concept of remote gaze estimate using deep learning has demonstrated promising results in analyzing client behavior in retail due to its scalability, resilience, cheap cost, and continuous nature.