Results 71 to 80 of about 52,284 (313)
Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net
, 2018 Models applied on real time response task, like click-through rate (CTR) prediction model, require high accuracy and rigorous response time. Therefore, top-performing deep models of high depth and complexity are not well suited for these applications ...
Bian, Weijie +5 more
core +1 more source
Real‐time semantic segmentation network for crops and weeds based on multi‐branch structure
IET Computer VisionWeed recognition is an inevitable problem in smart agriculture, and to realise efficient weed recognition, complex background, insufficient feature information, varying target sizes and overlapping crops and weeds are the main problems to be solved.
Yufan Liu +6 more
doaj +1 more source
Diagnostics, 2022 Neuroendocrine neoplasms (NENs) and tumors (NETs) are rare neoplasms that may affect any part of the gastrointestinal system. In this scoping review, we attempt to map existing evidence on the role of artificial intelligence, machine learning and deep ...
Athanasios G. Pantelis +2 more
doaj +1 more source
CE-Dedup: Cost-Effective Convolutional Neural Nets Training based on Image Deduplication [PDF]
, 2021 Xuan Li, Liqiong Chang, Xue Liu
openalex +1 more source
DA$^{\textbf{2}}$-Net : Diverse & Adaptive Attention Convolutional Neural Network
, 2021 Standard Convolutional Neural Network (CNN) designs rarely focus on the importance of explicitly capturing diverse features to enhance the network's performance. Instead, most existing methods follow an indirect approach of increasing or tuning the networks' depth and width, which in many cases significantly increases the computational cost.
Girma, Abenezer +4 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon +9 more
wiley +1 more source
Learning long-range spatial dependencies with horizontal gated-recurrent units
, 2018 Progress in deep learning has spawned great successes in many engineering applications. As a prime example, convolutional neural networks, a type of feedforward neural networks, are now approaching -- and sometimes even surpassing -- human accuracy on a ...
Kim, Junkyung +3 more
core +1 more source
Non‐stationary financial time series forecasting based on meta‐learning
Electronics Letters, 2023 In this letter, the authors address the challenge in forecasting non‐stationary financial time series by proposing a meta‐learning based forecasting model equipped with a convolution neural network (CNN) predictor and a long short‐term memory (LSTM) meta‐
Anqi Hong +3 more
doaj +1 more source
Convolutional deep rectifier neural nets for phone recognition [PDF]
Interspeech 2013, 2013 Rectifier neurons differ from standard ones only in that the sigmoid activation function is replaced by the rectifier function, max(0, x). Several recent studies suggest that rectifier units may be more suitable building units for deep nets. For example, we found that with deep rectifier networks one can attain a similar speech recognition performance ...
openaire +1 more source
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Advanced Functional Materials, EarlyView.Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source