A comprehensive survey on radio frequency (rf) fingerprinting: Traditional approaches, deep learning, and open challenges
Fifth generation (5G) network and beyond envision massive Internet of Things (IoT) rollout to
support disruptive applications such as extended reality (XR), augmented/virtual reality …
support disruptive applications such as extended reality (XR), augmented/virtual reality …
[HTML][HTML] Convolutional neural networks for vision neuroscience: Significance, developments, and outstanding issues
Convolutional Neural Networks (CNN) are a class of machine learning models
predominately used in computer vision tasks and can achieve human-like performance …
predominately used in computer vision tasks and can achieve human-like performance …
Performance vs. competence in human–machine comparisons
C Firestone - Proceedings of the National Academy of …, 2020 - National Acad Sciences
Does the human mind resemble the machines that can behave like it? Biologically inspired
machine-learning systems approach “human-level” accuracy in an astounding variety of …
machine-learning systems approach “human-level” accuracy in an astounding variety of …
Deep learning-based cardiovascular image diagnosis: a promising challenge
Artificial intelligence (AI) is becoming a vital concept in medicine leading to a rapid
emergence of important tools for medical diagnostics. Now, as a crucial machine learning …
emergence of important tools for medical diagnostics. Now, as a crucial machine learning …
HiCLIP: Contrastive language-image pretraining with hierarchy-aware attention
The success of large-scale contrastive vision-language pretraining (CLIP) has benefited
both visual recognition and multimodal content understanding. The concise design brings …
both visual recognition and multimodal content understanding. The concise design brings …
[HTML][HTML] Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks
The discovery that deep convolutional neural networks (DCNNs) achieve human
performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties …
performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties …
Remote sensing image superresolution using deep residual channel attention
JM Haut, R Fernandez-Beltran… - … on Geoscience and …, 2019 - ieeexplore.ieee.org
The current trend in remote sensing image superresolution (SR) is to use supervised deep
learning models to effectively enhance the spatial resolution of airborne and satellite-based …
learning models to effectively enhance the spatial resolution of airborne and satellite-based …
Stable maintenance of multiple representational formats in human visual short-term memory
Visual short-term memory (VSTM) enables humans to form a stable and coherent
representation of the external world. However, the nature and temporal dynamics of the …
representation of the external world. However, the nature and temporal dynamics of the …
Mind the gap: Challenges of deep learning approaches to theory of mind
Abstract Theory of Mind (ToM) is an essential ability of humans to infer the mental states of
others. Here we provide a coherent summary of the potential, current progress, and …
others. Here we provide a coherent summary of the potential, current progress, and …
A new pairwise deep learning feature for environmental microorganism image analysis
Environmental microorganism (EM) offers a highly efficient, harmless, and low-cost solution
to environmental pollution. They are used in sanitation, monitoring, and decomposition of …
to environmental pollution. They are used in sanitation, monitoring, and decomposition of …