Results 101 to 110 of about 4,047,749 (292)
Design and Investigation of Capsule Networks for Sentence Classification
Applied Sciences, 2019 In recent years, convolutional neural networks (CNNs) have been used as an alternative to recurrent neural networks (RNNs) in text processing with promising results.
Haftu Wedajo Fentaw, Tae-Hyong Kim
doaj +1 more source
HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image
CoRR, 2018 With the development of deep learning, the performance of hyperspectral image (HSI) classification has been greatly improved in recent years. The shortage of training samples has become a bottleneck for further improvement of performance. In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral ...
Yanan Luo +4 more
openaire +2 more sources
Advanced Science, EarlyView.Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Deep Learning-Based Spectrum Sensing for Cognitive Radio Applications
SensorsIn order for cognitive radios to identify and take advantage of unused frequency bands, spectrum sensing is essential. Conventional techniques for spectrum sensing rely on extracting features from received signals at specific locations.
Sara E. Abdelbaset +4 more
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Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Advanced Science, EarlyView.Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang +5 more
wiley +1 more source
State-of-the-Art of Breast Cancer Diagnosis in Medical Images via Convolutional Neural Networks (CNNs). [PDF]
J Healthc Inform Res, 2023 Harrison P, Hasan R, Park K.
europepmc +1 more source
Comparing Incremental Learning Strategies for Convolutional Neural Networks
, 2016 In the last decade, Convolutional Neural Networks (CNNs) have shown to perform incredibly well in many computer vision tasks such as object recognition and object detection, being able to extract meaningful high-level invariant features.
LOMONACO, VINCENZO +5 more
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Advanced Science, EarlyView.A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei +7 more
wiley +1 more source
Training convolutional neural networks with the Forward–Forward Algorithm
Scientific ReportsRecent successes in image analysis with deep neural networks are achieved almost exclusively with Convolutional Neural Networks (CNNs), typically trained using the backpropagation (BP) algorithm.
Riccardo Scodellaro +3 more
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Advanced Science, EarlyView.Here, we present an optoelectronic synaptic memtransistor (OSMT) integrating photoresponsive IGZO with contact‐engineered HfO2, enabling electrically and optically tunable synaptic weights. The device demonstrates broad range of tunable conductance states and array‐level image processing, highlighting its potential for intelligent machine vision ...
Donghyun Kang +6 more
wiley +1 more source