Data scarcity is a major challenge when training deeplearning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications …
… Furthermore, as artificial intelligence (AI), especially machine learning and deeplearning, has … Finally, opportunities and challenges in the clinical implementation of AI are discussed. …
L Zhang, L Zhang - IEEE Geoscience and Remote Sensing …, 2022 - ieeexplore.ieee.org
… With the development of big data, deeplearning (DL), large-… This review focuses not only machine learning and DL (which … Lefevre, “Deeplearning for classification of hyperspectral …
Y Cao, TA Geddes, JYH Yang, P Yang - Nature Machine Intelligence, 2020 - nature.com
… key developments in ensemble deeplearning and look at … deeplearning in bioinformatics is diverse and multifaceted, we identify and discuss the common challenges and opportunities …
PC Tiwari, R Pal, MJ Chaudhary… - Drug Development …, 2023 - Wiley Online Library
… discovery is held by the utilization of deeplearning, a subset of AI. By employing neural networks to analyze intricate data sets, deeplearning can unveil novel drug targets, optimize …
… The selection focused on works discussing the applications, opportunities, challenges, and future directions of ensemble learning within both deeplearning and machine learning …
… Even with this defense measures, it is hard to find the malicious participants owing to the secure aggregation techniques and capacity of the deeplearning model. Also FL framework …
… machine learning field, such as deeplearning and … Learning: algorithm, state, action, reward, and environment. Last, we discuss the current challenges and future research opportunities …
… They also discussed the challenges for the deeplearning. … The challenges offered by big data were timely and provided many opportunities and searches for the deeplearning. Gheisari …