[PDF] Top 20 Deep learning-based methods for parametric shape prediction
Has 10000 "Deep learning-based methods for parametric shape prediction" found on our website. Below are the top 20 most common "Deep learning-based methods for parametric shape prediction".
Deep learning-based methods for parametric shape prediction
... Finally, this structure admits closed-form expressions for normals and other geometric features, which can be used to construct loss functions that improve reconstructi[r] ... Voir le document complet
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Deep Learning Based Traffic Signs Boundary Estimation
... the shape of objects to detect) transformation matrices which transforms regressed bounding box corners to the template corners of the corresponding ...mations for the final prediction, finally, the ... Voir le document complet
7
Uncertainty-Aware Deep Learning Architectures for Highly Dynamic Air Quality Prediction
... art methods for air pollution prediction where many top-level articles were discussed and ...spatio-temporal deep learning model based on ConvLSTM for high dynamic air ... Voir le document complet
15
Genome-wide prediction of cis-regulatory regions using supervised deep learning methods
... other deep learning models might be well suited to improve annota- tions of non-coding ...cohorts for specific ...RNN- based models for prediction of enhancers using sequence ... Voir le document complet
15
A comparative analysis of machine/deep learning models for parking space availability prediction
... ML/DL methods, one technical problem is to identify the most suitable ML/DL model for the problem and the data set, as the performance of each ML/DL model varies from problem to problem and data set to data ... Voir le document complet
18
Computational Advantages of Deep Prototype-Based Learning
... prototype-based learning, pattern recognition, deep learn- ing, incremental learning 1 Introduction This study is conducted in the field of prototype-based machine learning, and ... Voir le document complet
8
Variance Based Samples Weighting for Supervised Deep Learning
... and for different purposes. While curriculum learning (Bengio et ...paced learning (Kumar et ...the learning could accelerate ...the prediction of each point throughout the training to ... Voir le document complet
23
Learning Methods for RSSI-based Geolocation: A Comparative Study
... The shape of the likelihood, is based on a model assump- tion, of Naive Bayes type: given the emiter position, the coordinates of the RSSI vector are ... Voir le document complet
6
Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives
... order for clinicians to be able to detect such biases, and alter the model accord- ingly [ 27 ...concept-extraction based models that are specifically tailored to a given ...concept-extraction based ... Voir le document complet
20
Direct shape optimization through deep reinforcement learning
... tackle shape optimization problems, namely gradient-based and gradient-free ...Gradient-based methods rely on the evaluation of ∇ x J, the gradient of the objec- tive function J with respect ... Voir le document complet
17
Deep learning for computational phenotyping in cell-based assays
... tool for the discovery and characterisation of ...MOA prediction performance according to a statistically rigorous ...baselines. For this, we propose multitask autoencoders, including a ... Voir le document complet
207
Deep Learning vs. Kernel Methods: Performance for Emotion Prediction in Videos
... of deep learning, the performances in scene and object recognition have been progressing ...emotion prediction, stagnate at moderate ...in deep learning? This paper proposes to ... Voir le document complet
8
Deep learning for cloud detection
... approaches for cloud detection, that are mostly based on machine learning and hand crafted features, have shown lack of ro- ...recognition, deep learning methods have shown ... Voir le document complet
7
Medical-based Deep Curriculum Learning for Improved Fracture Classification
... Dataset. Our in-house dataset consists of anonymized X-rays of the hip and pelvis collected at the trauma surgery department of the Rechts der Isar Hos- pital in Munich. The studies contain lateral view and ... Voir le document complet
10
Parametric shape modeler for hulls and appendages
... deformation for ships is a relatively recent ...classical methods created for 3D animations purposes, and they have been applied to shape optimization for ...whole shape of the ... Voir le document complet
11
Comparison of multiobjective gradient-based methods for structural shape optimization
... gradient-based methods, a good approximation of the Pareto front is achieved and the overall performances strongly improve with respect to Pareto Archived Evolutionary ... Voir le document complet
30
Learning sparse spline-based shape models
... the shape of objects as “what is left after removing information of posi- tion, scale and orientation” following the seminal definition of ...define shape as equiva- lence classes with respect to some ... Voir le document complet
119
Efficient FPGA-Based Inference Architectures for Deep Learning Networks
... device. Moreover, the synthesis, place and route processes of the design on FPGAs take time and these processes should be repeated after each new design. There have been several attempts to implement both the ... Voir le document complet
117
Distribution-Based Invariant Deep Networks for Learning Meta-Features
... A large number of meta-features have been manually designed along the years [24], ranging from sufficient statistics to the so-called landmarks [28], computing the performance of fast ML algorithms on the considered ... Voir le document complet
30
Learning-Based Matheuristic Solution Methods for Stochastic Network Design
... methods for SMCFND problems ...function. For example, Thapalia et al. [116, 117, 118] have shown that for the single-commodity network design problem, certain structural patterns from the ... Voir le document complet
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