Fully hardware-implemented memristor convolutional neural network
Memristor-enabled neuromorphic computing systems provide a fast and energy-efficient
approach to training neural networks 1 , 2 , 3 – 4 . However, convolutional neural networks (…
approach to training neural networks 1 , 2 , 3 – 4 . However, convolutional neural networks (…
Neuro-inspired computing chips
The rapid development of artificial intelligence (AI) demands the rapid development of
domain-specific hardware specifically designed for AI applications. Neuro-inspired computing …
domain-specific hardware specifically designed for AI applications. Neuro-inspired computing …
A durable and safe solid-state lithium battery with a hybrid electrolyte membrane
W Zhang, J Nie, F Li, ZL Wang, C Sun - Nano Energy, 2018 - Elsevier
Polymer–ceramic composite electrolytes are emerging as a promising solution to achieving
high ionic conductivity, optimal mechanical properties, and good safety for developing high-…
high ionic conductivity, optimal mechanical properties, and good safety for developing high-…
Face classification using electronic synapses
Conventional hardware platforms consume huge amount of energy for cognitive learning
due to the data movement between the processor and the off-chip memory. Brain-inspired …
due to the data movement between the processor and the off-chip memory. Brain-inspired …
A compute-in-memory chip based on resistive random-access memory
Realizing increasingly complex artificial intelligence (AI) functionalities directly on edge
devices calls for unprecedented energy efficiency of edge hardware. Compute-in-memory (CIM) …
devices calls for unprecedented energy efficiency of edge hardware. Compute-in-memory (CIM) …
A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of physical …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of physical …
Onetracker: Unifying visual object tracking with foundation models and efficient tuning
Visual object tracking aims to localize the target object of each frame based on its initial
appearance in the first frame. Depending on the input modility tracking tasks can be divided into …
appearance in the first frame. Depending on the input modility tracking tasks can be divided into …
A review of high temperature co-electrolysis of H 2 O and CO 2 to produce sustainable fuels using solid oxide electrolysis cells (SOECs): advanced materials and …
…, B Yu, W Zhang, J Chen, J Qiao, J Zhang - Chemical Society …, 2017 - pubs.rsc.org
High-temperature solid oxide electrolysis cells (SOECs) are advanced electrochemical
energy storage and conversion devices with high conversion/energy efficiencies. They offer …
energy storage and conversion devices with high conversion/energy efficiencies. They offer …
Topformer: Token pyramid transformer for mobile semantic segmentation
Although vision transformers (ViTs) have achieved great success in computer vision, the
heavy computational cost hampers their applications to dense prediction tasks such as …
heavy computational cost hampers their applications to dense prediction tasks such as …
Magis: Llm-based multi-agent framework for github issue resolution
In software development, resolving the emergent issues within GitHub repositories is a complex
challenge that involves not only the incorporation of new code but also the maintenance …
challenge that involves not only the incorporation of new code but also the maintenance …