Siddhartha Chandra
Siddhartha Chandra
Amazon Lab 126
Email confirmado em - Página inicial
Citado por
Citado por
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
Fast, exact and multi-scale inference for semantic image segmentation with deep gaussian crfs
S Chandra, I Kokkinos
European conference on computer vision, 402-418, 2016
Dense and low-rank gaussian crfs using deep embeddings
S Chandra, N Usunier, I Kokkinos
Proceedings of the IEEE International Conference on Computer Vision, 5103-5112, 2017
Learning to generate synthetic data via compositing
S Tripathi, S Chandra, A Agrawal, A Tyagi, JM Rehg, V Chari
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Deep spatio-temporal random fields for efficient video segmentation
S Chandra, C Couprie, I Kokkinos
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
Context aware 3D CNNs for brain tumor segmentation
S Chandra, M Vakalopoulou, L Fidon, E Battistella, T Estienne, R Sun, ...
International MICCAI Brainlesion Workshop, 299-310, 2018
Box2seg: Attention weighted loss and discriminative feature learning for weakly supervised segmentation
V Kulharia, S Chandra, A Agrawal, P Torr, A Tyagi
European Conference on Computer Vision, 290-308, 2020
Deep learning-based concurrent brain registration and tumor segmentation
T Estienne, M Lerousseau, M Vakalopoulou, E Alvarez Andres, ...
Frontiers in computational neuroscience 14, 17, 2020
Accurate human-limb segmentation in RGB-D images for intelligent mobility assistance robots
S Chandra, S Tsogkas, I Kokkinos
Proceedings of the IEEE International Conference on Computer Vision …, 2015
Human joint angle estimation and gesture recognition for assistive robotic vision
A Guler, N Kardaris, S Chandra, V Pitsikalis, C Werner, K Hauer, ...
European Conference on Computer Vision, 415-431, 2016
Learning multiple non-linear sub-spaces using k-rbms
S Chandra, S Kumar, CV Jawahar
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
Learning hierarchical bag of words using naive bayes clustering
S Chandra, S Kumar, CV Jawahar
Asian Conference on Computer Vision, 382-395, 2012
Structured output prediction and learning for deep monocular 3D human pose estimation
S Kinauer, RA Güler, S Chandra, I Kokkinos
International Workshop on Energy Minimization Methods in Computer Vision and …, 2017
Sparse discriminative Fisher vectors in visual classification
V Garg, S Chandra, CV Jawahar
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and …, 2012
Surface based object detection in rgbd images
S Chandra, G Chrysos, I Kokkinos
British Machine Vision Conference, 2016
Smartphone Camera Based Assessment of Adiposity: A Multi-Site Validation Study
MD Majmudar, S Chandra, S Kennedy, A Agrawal, M Sippel, P Ramu, ...
medRxiv, 2021
Generation of synthetic image data for computer vision models
A Tyagi, AK Agrawal, S Chandra, VUK Chari, S Tripathi, J Rehg
US Patent 10,860,836, 2020
Generation of synthetic image data using three-dimensional models
S Tripathi, V Chari, A Tyagi, AK Agrawal, J Rehg, S Chandra
US Patent 10,909,349, 2021
Proof of Correctness and Time Complexity Analysis of a Maximum Distance Transform Algorithm
M Sahasrabudhe, S Chandra
arXiv preprint arXiv:1908.01662, 2019
Apprentissage Profond pour des Prédictions Structurées Efficaces appliqué à la Classification Dense en Vision par Ordinateur
S Chandra
Université Paris-Saclay (ComUE), 2018
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