Suchergebnisse - Computer Learning and Pattern Recognition::Evolutionary Computing*

Hand-Gesture Recognition Based on EMG and Event-Based Camera Sensor Fusion: A Benchmark in Neuromorphic Computing von Ceolini, Enea, Frenkel, Charlotte, Shrestha, Sumit Bam, Taverni, Gemma, Khacef, Lyes, Payvand, Melika, Donati, Elisa

“… Nowadays, with the increasing use of technology, hand-gesture recognition is considered to be an important aspect of Human-Machine Interaction (HMI …”
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Interpolation consistency training for semi-supervised learning von Verma, Vikas, Kawaguchi, Kenji, Lamb, Alex, Kannala, Juho, Solin, Arno, Bengio, Yoshua, Lopez-Paz, David

“… We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm …”
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Explainability in deep reinforcement learning von Heuillet, Alexandre, Couthouis, Fabien, Díaz-Rodríguez, Natalia

“… for reinforcement learning (RL), has not been extensively studied. We review recent works in the direction to attain Explainable Reinforcement Learning (XRL …”
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Deep Learning for Classification of Hyperspectral Data: A Comparative Review von Audebert, Nicolas, Le Saux, Bertrand, Lefevre, Sebastien

“… In recent years, deep-learning techniques revolutionized the way remote sensing data are processed …”
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Artificial Intelligence and Data Analytics for Energy Exploration and Production von Fred Aminzadeh, Cenk Temizel, Yasin Hajizadeh

“… , evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural …”
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Learning Accurate Performance Predictors for Ultrafast Automated Model Compression von Wang, Ziwei, Lu, Jiwen, Xiao, Han, Liu, Shengyu, Zhou, Jie

“… In this paper, we propose an ultrafast automated model compression framework called SeerNet for flexible network deployment. Conventional non-differen-tiable …”
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Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms von Moebel, Emmanuel, Martinez-Sanchez, Antonio, Lamm, Lorenz, Righetto, Ricardo D, Wietrzynski, Wojciech, Albert, Sahradha, Larivière, Damien, Fourmentin, Eric, Pfeffer, Stefan, Ortiz, Julio, Baumeister, Wolfgang, Peng, Tingying, Engel, Benjamin D, Kervrann, Charles

“… s. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes …”
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Learning to compare image patches via convolutional neural networks von Zagoruyko, Sergey, Komodakis, Nikos

“… ) a general similarity function for comparing image patches, which is a task of fundamental importance for many computer vision problems …”
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Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy von Ben naceur, Mostefa, Akil, Mohamed, Saouli, Rachida, Kachouri, Rostom

“… •A novel fully automatic Deep Convolutional Neural Networks model for brain tumor segmentation.•The model is inspired by the Occipito-Temporal Pathway …”
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Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks von Audebert, Nicolas, Le Saux, Bertrand, Lefèvre, Sébastien

“… Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning …”
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Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images von naceur, Mostefa Ben, Saouli, Rachida, Akil, Mohamed, Kachouri, Rostom

“… •A new fully automatic end-to-end deep learning model for brain tumor segmentation …”
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Reducing environment exposure to COVID-19 by IoT sensing and computing with deep learning von Ma, Chendong, Song, Jun, Xu, Yibo, Fan, Hongwei, Liu, Xiaoran, Wu, Xing, Luo, Yang, Sun, Tuo, Xie, Jiemin

“… in: Computer vision and pattern recognition, 2015). We achieved …”
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Deep Representation-Based Feature Extraction and Recovering for Finger-Vein Verification von Qin, Huafeng, El-Yacoubi, Mounim A.

“… This paper proposes a deep learning model to extract and recover vein features using limited a priori knowledge …”
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Unsupervised visual feature learning with spike-timing-dependent plasticity: How far are we from traditional feature learning approaches? von Falez, Pierre, Tirilly, Pierre, Bilasco, Ioan Marius, Devienne, Philippe, Boulet, Pierre

“… •We compare the performance of spiking neural networks (SNNs) with auto-encoders for visual feature learning …”
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Diabetic retinopathy detection using red lesion localization and convolutional neural networks von Zago, Gabriel Tozatto, Andreão, Rodrigo Varejão, Dorizzi, Bernadette, Teatini Salles, Evandro Ottoni

“… Detecting the early signs of diabetic retinopathy (DR) is essential, as timely treatment might reduce or even prevent vision loss. Moreover, automatically …”
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A Deep learning method for accurate and fast identification of coral reef fishes in underwater images von Villon, Sébastien, Mouillot, David, Chaumont, Marc, Darling, Emily S., Subsol, Gérard, Claverie, Thomas, Villéger, Sébastien

“… Identifying and counting fish individuals on photos and videos is a crucial task to cost-effectively monitor marine biodiversity, yet it remains difficult and …”
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High-level prior-based loss functions for medical image segmentation: A survey von El Jurdi, Rosana, Petitjean, Caroline, Honeine, Paul, Cheplygina, Veronika, Abdallah, Fahed

“… Today, deep convolutional neural networks (CNNs) have demonstrated state of the art performance for supervised medical image segmentation, across various …”
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From artificial neural networks to deep learning for music generation: history, concepts and trends von Briot, Jean-Pierre

“… , for weather prediction and pattern recognition), but has already conquered other areas, such as translation …”
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Semi-supervised semantic segmentation in Earth Observation: the MiniFrance suite, dataset analysis and multi-task network study von Castillo-Navarro, Javiera, Le Saux, Bertrand, Boulch, Alexandre, Audebert, Nicolas, Lefèvre, Sébastien

“… The development of semi-supervised learning techniques is essential to enhance the generalization capacities of machine learning algorithms …”
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Effective training of convolutional neural networks for face-based gender and age prediction von Antipov, Grigory, Baccouche, Moez, Berrani, Sid-Ahmed, Dugelay, Jean-Luc

“… •Distribution label encoding as an optimal way to represent age in a CNN.•Role of pretraining in selection of the CNN architecture and the training …”
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