Deep learning: systematic review, models, challenges, and research directions
Abstract The current development in deep learning is witnessing an exponential transition into automation applications. This automation transition can provide a promising framework for higher performance and lower complexity. This ongoing transition undergoes several rapid changes, resulting in the processing of the data by several studies, while it may lead to time-consuming and costly models. Thus, to address these challenges, several studies have been conducted to investigate deep learning te
Record details
Published: 7 September 2023
Source: OpenAlex
Category: Research
Topics: Jobs & economy · Finance, VC & PE
Retrieved: 14 July 2026
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ethics.ai (7 September 2023), “Deep learning: systematic review, models, challenges, and research directions,” evidence record 9399, https://ethics.ai/record/9399 (originally published by OpenAlex).
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