AIMC Topic: Semiconductors

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Power and Area Efficient Cascaded Effectless GDI Approximate Adder for Accelerating Multimedia Applications Using Deep Learning Model.

Computational intelligence and neuroscience Mar 19, 2022
Approximate computing is an upsurging technique to accelerate the process through less computational effort while keeping admissible accuracy of error-tolerant applications such as multimedia and deep learning. Inheritance properties of the deep lear...
Deep Learning Diffusion Computer Simulation Multimedia Semiconductors
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In-Field Detection of American Foulbrood (AFB) by Electric Nose Using Classical Classification Techniques and Sequential Neural Networks.

Sensors (Basel, Switzerland) Feb 2, 2022
American foulbrood is a dangerous bee disease that attacks the sealed brood. It quickly leads to the death of bee colonies. Efficient diagnosis of this disease is essential. As specific odours are produced when larvae rot, it was investigated whether...
Larva United States Neural Networks, Computer Animals Bees Electronic Nose Bayes Theorem Semiconductors
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High Accuracy Real-Time Multi-Gas Identification by a Batch-Uniform Gas Sensor Array and Deep Learning Algorithm.

ACS sensors Jan 18, 2022
Semiconductor metal oxide (SMO) gas sensors are attracting great attention as next-generation environmental monitoring sensors. However, there are limitations to the actual application of SMO gas sensors due to their low selectivity. Although the ele...
Environmental Monitoring Oxides Semiconductors Electronic Nose Deep Learning
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Advanced Recovery and High-Sensitive Properties of Memristor-Based Gas Sensor Devices Operated at Room Temperature.

ACS sensors Nov 16, 2021
Fast recovery, high sensitivity, high selectivity, and room temperature (RT) sensing characteristics of NO gas sensors are essential for environmental monitoring, artificial intelligence, and inflammatory diagnosis of asthma patients. However, the co...
Temperature Semiconductors Artificial Intelligence Gases Humans
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CMOS Implementation of ANNs Based on Analog Optimization of N-Dimensional Objective Functions.

Sensors (Basel, Switzerland) Oct 25, 2021
The design of neural network architectures is carried out using methods that optimize a particular objective function, in which a point that minimizes the function is sought. In reported works, they only focused on software simulations or commercial ...
Oxides Neurons Semiconductors Neural Networks, Computer Algorithms
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An artificial neural network chip based on two-dimensional semiconductor.

Science bulletin Oct 5, 2021
Recently, research on two-dimensional (2D) semiconductors has begun to translate from the fundamental investigation into rudimentary functional circuits. In this work, we unveil the first functional MoS artificial neural network (ANN) chip, including...
Children's Health Insurance Program Semiconductors Computer Simulation Molybdenum Neural Networks, Computer
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Bandgap prediction of two-dimensional materials using machine learning.

PloS one Aug 13, 2021
The bandgap of two-dimensional (2D) materials plays an important role in their applications to various devices. For instance, the gapless nature of graphene limits the use of this material to semiconductor device applications, whereas the indirect ba...
Semiconductors Graphite Molybdenum Electric Conductivity Boron Compounds Databases, Chemical Disulfides Machine Learning Models, Statistical
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A Low-Power Spiking Neural Network Chip Based on a Compact LIF Neuron and Binary Exponential Charge Injector Synapse Circuits.

Sensors (Basel, Switzerland) Jun 29, 2021
To realize a large-scale Spiking Neural Network (SNN) on hardware for mobile applications, area and power optimized electronic circuit design is critical. In this work, an area and power optimized hardware implementation of a large-scale SNN for real...
Synapses Neural Networks, Computer Computers Neurons Semiconductors
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Dielectric Engineered Two-Dimensional Neuromorphic Transistors.

Nano letters Apr 9, 2021
Two-dimensional (2D) materials, which exhibit planar-wafer technique compatibility and pure electrically triggered communication, have established themselves as potential candidates in neuromorphic architecture integration. However, the current 2D ar...
Neural Networks, Computer Semiconductors Synapses Oxides
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Neuromorphic Binarized Polariton Networks.

Nano letters Feb 26, 2021
The rapid development of artificial neural networks and applied artificial intelligence has led to many applications. However, current software implementation of neural networks is severely limited in terms of performance and energy efficiency. It is...
Brain Neurons Semiconductors Neural Networks, Computer Artificial Intelligence Humans
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