Deep learning has become the mainstream technology in computer vision, and it has received extensive research interest in developing new medical image processing algorithms to support disease detection and diagnosis.
Sound event detection is an important facet of audio tagging that aims to identify sounds of interest and define both the sound category and time boundaries for each sound event
Early detection of brain metastases (BM) is one of the determining factors for the successful treatment of patients with cancer; however, the accurate detection of small BM lesions (< 15mm)
In certain systems which are subject to significant constant external forcing such as an airplane in wind or an underwater glider in ocean currents, the ability to detect the forcing
Offline model learning for planning is a branch of machine learning that trains agents to perform actions in an unknown environment using a fixed batch of previously collected experiences. The
This paper develops a novel methodology for designing analog beamforming codebooks for full-duplex millimeter wave (mmWave) transceivers, the first such codebooks to the best of our knowledge. Our design reduces
This paper presents a comparative evaluation of central and self-dispatch management concepts for battery energy storage (BES) facilities in island power systems with a high renewable energy source (RES) penetration.
This letter investigates a Branching Dueling Q-Network (BDQ) based online operation strategy for a microgrid with distributed battery energy storage systems (BESSs) operating under uncertainties. The developed deep reinforcement learning
In closed-loop wireless control systems, the state-of-the-art approach prescribes that a controller receives by wireless communications the individual sensor measurements, and then sends the computed control signal to the actuators.
Recent studies show promising performance gains achieved by non-linear equalization using neural networks (NNs) over traditional linear equalization in two-dimensional magnetic recording (TDMR) channels. But the examined neural network architectures