… With the development of big data, deep learning (DL), large-… This review focuses not only
machine learning and DL (which … Lefevre, “Deep learning for classification of hyperspectral …

… key developments in ensemble deep learning and look at … deep learning in bioinformatics
is diverse and multifaceted, we identify and discuss the common challenges and opportunities …

… In the past decades, computer audition (CA), as an emerging interdisciplinary subject that
includes acoustics, signal processing, machine learning, and deep learning technologies to …

… discovery is held by the utilization of deep learning, a subset of AI. By employing neural
networks to analyze intricate data sets, deep learning can unveil novel drug targets, optimize …

… Deep learning is a type of machine learning that uses neural networks with multiple layers
to process complex data such as images or speech [3]. Natural language processing is the …

… The next big leap, deep learning, marked a transformation … ChatGPT presents opportunities
and challenges for software … Conversely, the deep learning revolution is reshaping NLP, …

… Even with this defense measures, it is hard to find the malicious participants owing to the
secure aggregation techniques and capacity of the deep learning model. Also FL framework …

… machine learning field, such as deep learning and … Learning: algorithm, state, action, reward,
and environment. Last, we discuss the current challenges and future research opportunities …

… has become a topic of interest, with advanced deep learning technologies showing promising
results [51]. Although we also focus on deep learning for IoT, we are more interested in its …

… They also discussed the challenges for the deep learning. … The challenges offered by big
data were timely and provided many opportunities and searches for the deep learning. Gheisari …