Evolution of autonomous and semi‐autonomous robotic surgical systems: a review of the literature
GP Moustris, SC Hiridis… - … journal of medical …, 2011 - Wiley Online Library
Background Autonomous control of surgical robotic platforms may offer enhancements such
as higher precision, intelligent manoeuvres, tissue‐damage avoidance, etc. Autonomous …
as higher precision, intelligent manoeuvres, tissue‐damage avoidance, etc. Autonomous …
Long short-term memory networks in memristor crossbar arrays
Recent breakthroughs in recurrent deep neural networks with long short-term memory
(LSTM) units have led to major advances in artificial intelligence. However, state-of-the-art …
(LSTM) units have led to major advances in artificial intelligence. However, state-of-the-art …
Decision making in multiagent systems: A survey
Y Rizk, M Awad, EW Tunstel - IEEE Transactions on Cognitive …, 2018 - ieeexplore.ieee.org
Intelligent transport systems, efficient electric grids, and sensor networks for data collection
and analysis are some examples of the multiagent systems (MAS) that cooperate to achieve …
and analysis are some examples of the multiagent systems (MAS) that cooperate to achieve …
Time series forecasting using LSTM networks: A symbolic approach
S Elsworth, S Güttel - arXiv preprint arXiv:2003.05672, 2020 - arxiv.org
Machine learning methods trained on raw numerical time series data exhibit fundamental
limitations such as a high sensitivity to the hyper parameters and even to the initialization of …
limitations such as a high sensitivity to the hyper parameters and even to the initialization of …
GRU-based deep learning approach for network intrusion alert prediction
The exponential growth in the number of cyber attacks in the recent past has necessitated
active research on network intrusion detection, prediction and mitigation systems. While …
active research on network intrusion detection, prediction and mitigation systems. While …
Nonlinear autoregressive neural network in an energy management strategy for battery/ultra-capacitor hybrid electrical vehicles
Hybrid electric vehicles are one of the most promising solutions for reducing pollution and
fuel consumption. However, their propulsion system comprises a number of different …
fuel consumption. However, their propulsion system comprises a number of different …
Computationally expedient Photovoltaic power Forecasting: A LSTM ensemble method augmented with adaptive weighting and data segmentation technique
Photovoltaics (PVs) hold the promise of sustainable electricity production. However, PV
output is significantly influenced by variations in terrestrial solar radiation and other weather …
output is significantly influenced by variations in terrestrial solar radiation and other weather …
Evolutionary computation for reinforcement learning
S Whiteson - Reinforcement Learning: State-of-the-art, 2012 - Springer
Algorithms for evolutionary computation, which simulate the process of natural selection to
solve optimization problems, are an effective tool for discovering high-performing …
solve optimization problems, are an effective tool for discovering high-performing …
A system for robotic heart surgery that learns to tie knots using recurrent neural networks
Tying suture knots is a time-consuming task performed frequently during minimally invasive
surgery (MIS). Automating this task could greatly reduce total surgery time for patients …
surgery (MIS). Automating this task could greatly reduce total surgery time for patients …