Opportunities and challenges in explainable artificial intelligence (xai): A survey
Nowadays, deep neural networks are widely used in mission critical systems such as
healthcare, self-driving vehicles, and military which have direct impact on human lives …
healthcare, self-driving vehicles, and military which have direct impact on human lives …
Machine and deep learning for resource allocation in multi-access edge computing: A survey
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
Self-correcting deep learning for estimating rice leaf nitrogen concentration with mobile phone images
As a pivotal role in crop development, the application of nitrogen fertilizers enhances yields,
while excessive use poses environmental risks. Precision nitrogen management requires …
while excessive use poses environmental risks. Precision nitrogen management requires …
Transfer learning for the efficient detection of COVID-19 from smartphone audio data
Disease detection from smartphone data represents an open research challenge in mobile
health (m-health) systems. COVID-19 and its respiratory symptoms are an important case …
health (m-health) systems. COVID-19 and its respiratory symptoms are an important case …
AI-augmented behavior analysis for children with developmental disabilities: building toward precision treatment
Autism spectrum disorder is a developmental disorder characterized by significant social,
communication, and behavioral challenges. Individuals diagnosed with autism, intellectual …
communication, and behavioral challenges. Individuals diagnosed with autism, intellectual …
Model compression of deep neural network architectures for visual pattern recognition: Current status and future directions
Abstract Visual Pattern Recognition Networks (VPRNs) are widely used in various visual
data based applications such as computer vision and edge AI. VPRNs help to enhance a …
data based applications such as computer vision and edge AI. VPRNs help to enhance a …
Training Machine Learning models at the Edge: A Survey
Edge Computing (EC) has gained significant traction in recent years, promising enhanced
efficiency by integrating Artificial Intelligence (AI) capabilities at the edge. While the focus …
efficiency by integrating Artificial Intelligence (AI) capabilities at the edge. While the focus …
A survey on large language model acceleration based on kv cache management
H Li, Y Li, A Tian, T Tang, Z Xu, X Chen, N Hu… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) have revolutionized a wide range of domains such as
natural language processing, computer vision, and multi-modal tasks due to their ability to …
natural language processing, computer vision, and multi-modal tasks due to their ability to …
A Transfer Learning and Explainable Solution to Detect mpox from Smartphones images
Monkeypox (mpox) virus has become a “public health emergency of international concern”
in the last few months, as declared by the World Health Organization, especially for low …
in the last few months, as declared by the World Health Organization, especially for low …
Self-evolving integrated vertical heterogeneous networks
6G and beyond networks tend towards fully intelligent and adaptive design in order to
provide better operational agility in maintaining universal wireless access and supporting a …
provide better operational agility in maintaining universal wireless access and supporting a …