Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

L Alzubaidi, J Zhang, AJ Humaidi, A Al-Dujaili… - Journal of big Data, 2021 - Springer
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …

Breast cancer detection using deep learning: Datasets, methods, and challenges ahead

RA Dar, M Rasool, A Assad - Computers in biology and medicine, 2022 - Elsevier
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …

Evaluating recommender systems: survey and framework

E Zangerle, C Bauer - ACM Computing Surveys, 2022 - dl.acm.org
The comprehensive evaluation of the performance of a recommender system is a complex
endeavor: many facets need to be considered in configuring an adequate and effective …

Where to go next for recommender systems? id-vs. modality-based recommender models revisited

Z Yuan, F Yuan, Y Song, Y Li, J Fu, F Yang… - Proceedings of the 46th …, 2023 - dl.acm.org
Recommendation models that utilize unique identities (IDs for short) to represent distinct
users and items have been state-of-the-art (SOTA) and dominated the recommender …

Languagebind: Extending video-language pretraining to n-modality by language-based semantic alignment

B Zhu, B Lin, M Ning, Y Yan, J Cui, HF Wang… - arxiv preprint arxiv …, 2023 - arxiv.org
The video-language (VL) pretraining has achieved remarkable improvement in multiple
downstream tasks. However, the current VL pretraining framework is hard to extend to …

Recommender systems leveraging multimedia content

Y Deldjoo, M Schedl, P Cremonesi, G Pasi - ACM Computing Surveys …, 2020 - dl.acm.org
Recommender systems have become a popular and effective means to manage the ever-
increasing amount of multimedia content available today and to help users discover …

Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions

S Ahmad, I Shakeel, S Mehfuz, J Ahmad - Computer Science Review, 2023 - Elsevier
In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …

Current challenges and visions in music recommender systems research

M Schedl, H Zamani, CW Chen, Y Deldjoo… - International Journal of …, 2018 - Springer
Music recommender systems (MRSs) have experienced a boom in recent years, thanks to
the emergence and success of online streaming services, which nowadays make available …

A survey of active learning in collaborative filtering recommender systems

M Elahi, F Ricci, N Rubens - Computer Science Review, 2016 - Elsevier
In collaborative filtering recommender systems user's preferences are expressed as ratings
for items, and each additional rating extends the knowledge of the system and affects the …

Adaptive focus for efficient video recognition

Y Wang, Z Chen, H Jiang, S Song… - proceedings of the …, 2021 - openaccess.thecvf.com
In this paper, we explore the spatial redundancy in video recognition with the aim to improve
the computational efficiency. It is observed that the most informative region in each frame of …