Results 111 to 120 of about 9,899,096 (370)
Learning Abstract Classes using Deep Learning
, 2016 Humans are generally good at learning abstract concepts about objects and scenes (e.g.\ spatial orientation, relative sizes, etc.). Over the last years convolutional neural networks have achieved almost human performance in recognizing concrete classes ...
Piater, Justus +2 more
core +1 more source
2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC), 2020 Deep learning and other machine learning approaches are deployed to many systems related to Internet of Things or IoT. However, it faces challenges that adversaries can take loopholes to hack these systems through tampering history data. This paper first presents overall points of adversarial machine learning.
openaire +3 more sources
Opening the black box of deep learning [PDF]
arXiv, 2018 The great success of deep learning shows that its technology contains profound truth, and understanding its internal mechanism not only has important implications for the development of its technology and effective application in various fields, but also provides meaningful insights into the understanding of human brain mechanism.
arxiv
Transferability in Deep Learning: A Survey [PDF]
arXiv, 2022 The success of deep learning algorithms generally depends on large-scale data, while humans appear to have inherent ability of knowledge transfer, by recognizing and applying relevant knowledge from previous learning experiences when encountering and solving unseen tasks.
arxiv
Systematic profiling of cancer‐fibroblast interactions reveals drug combinations in ovarian cancer
Molecular Oncology, EarlyView.Fibroblasts, cells in the tumor environment, support ovarian cancer cell growth and alter morphology and drug response. We used fibroblast and cancer cell co‐culture models to test 528 drugs and discovered new drugs for combination treatment. We showed that adding Vorinostat or Birinapant to standard chemotherapy may improve drug response, suggesting ...
Greta Gudoityte +10 more
wiley +1 more source
Deep Learning for Action and Gesture Recognition in Image Sequences: A Survey [PDF]
, 2017 Interest in automatic action and gesture recognition has grown considerably in the last few years. This is due in part to the large number of application domains for this type of technology.
Asadi-Aghbolaghi, M +8 more
core
Concept-Oriented Deep Learning [PDF]
arXiv, 2018 Concepts are the foundation of human deep learning, understanding, and knowledge integration and transfer. We propose concept-oriented deep learning (CODL) which extends (machine) deep learning with concept representations and conceptual understanding capability.
arxiv
FEBS Open Bio, EarlyView.This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi +2 more
wiley +1 more source
Generalization in Deep Learning
, 2022 Published by Cambridge University Press.
Kawaguchi, Kenji +2 more
openaire +2 more sources
The Journal of Neuroscience, 2018 Animals successfully thrive in noisy environments with finite resources. The necessity to function with resource constraints has led evolution to design animal brains (and bodies) to be optimal in their use of computational power while being adaptable to their environmental niche.
Shyam Srinivasan +3 more
openaire +3 more sources