The solid electrolyte interphase (SEI) is a key component of a lithium-ion battery forming during the first few dischage/charge cycles at the interface between the anode and the electrolyte. The SEI passivates the anode-electrolyte interface by inhibiting ...
ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...
Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...
Herein, a fluoropolymer bifunctional solid membrane interface (SMI) for an aqueous Al-air battery is proposed, which inhibits anodic self-corrosion, while concurrently reducing the accumulation of undesirable by-products. A battery using the SMI exhibits a ...
The current study evaluates integrating fuel cell technology into the batteries as an alternative for internal combustion engines (ICEs) for Unmanned Aerial Vehicles (UAV). To further improve the performance of the UAV, a turbocharger is also integrated to ...
How does the visual system represent continuity in the constantly changing visual input? A recent proposal is that vision is serially dependent: Stimuli seen a moment ago influence what we perceive in the present. In line with this, recent frameworks sugge ...
The detection of digital face manipulation in video has attracted extensive attention due to the increased risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been developed and ha ...
We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photo-like images of fullbody humans with consistent appearances under different view-angles and body-poses. To tackle the representational and computational challenges in sy ...
Deep-learning-based digital twins (DDT) are a promising tool for data-driven system health management because they can be trained directly on operational data. A major challenge for efficient training however is that industrial datasets remain unlabeled. T ...
Epilepsy is a common chronic neurological disorder that causes recurring seizures and affects more than 50 million people worldwide. Implantable medical devices (IMDs) are regarded as effective tools to cure patients who suffer from refractory epilepsy. Se ...