Kandan Ramakrishnan

发表

Relationship Matters: Relation Guided Knowledge Transfer for Incremental Learning of Object Detectors

Quanfu Fan, Aude Oliva, Rameswar Panda, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Visual dictionaries in the Brain: Comparing HMAX and BOW

Arnold W. M. Smeulders, Iris I. A. Groen, Sennay Ghebreab, 2014, ICME.

Identifying Interpretable Action Concepts in Deep Networks

Aude Oliva, Dan Gutfreund, Rogerio Feris, 2019, CVPR Workshops.

Examining Class Dependant Sub-Paths in Deep Neural Networks

Aude Oliva, Mathew Monfort, Kandan Ramakrishnan, 2019, Journal of Vision.

Feature representations in networks trained with image sets of animate, inanimate or scenes differ in terms of computational filters but not in location in the brain

Cees G. M. Snoek, H. Steven Scholte, Kandan Ramakrishnan, 2016 .

Neural spatial consistency of hierarchical vision models

Arnold W. M. Smeulders, H. S. Scholte, Sennay Ghebreab, 2015, NIPS 2015.

Overlap in performance of CNN's, human behavior and EEG classification

Steven Scholte, Kandan Ramakrishnan, Max Losch, 2016 .

Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition pdf

Quanfu Fan, Chun-Fu Chen, Aude Oliva, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

What is unique in computational models of object recognition

Sennay Ghebreab, H. Steven Scholte, Kandan Ramakrishnan, 2016 .

Convolutional Neural Networks in the Brain: an fMRI study.

Sennay Ghebreab, Arnold Smeulders, Steven Scholte, 2015, Journal of vision.

Visual word representation in the brain

Arnold W. M. Smeulders, Iris I. A. Groen, Sennay Ghebreab, 2013, NIPS 2013.

The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence pdf

Yalda Mohsenzadeh, Aude Oliva, Kshitij Dwivedi, 2019, 2019 Conference on Cognitive Computational Neuroscience.

Large Scale Neural Architecture Search with Polyharmonic Splines pdf

Chun-Fu Chen, Michele Merler, Minsik Cho, 2020, ArXiv.

Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding pdf

Quanfu Fan, Aude Oliva, Dan Gutfreund, 2019, ArXiv.

NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search pdf

Chun-Fu Chen, Michele Merler, Minsik Cho, 2020, ArXiv.

Visual pathways from the perspective of cost functions and multi-task deep neural networks

Sander M. Bohte, H. Steven Scholte, Kandan Ramakrishnan, 2017, Cortex.

CNNs trained on places and animacy explain different patterns of variance for the same dataset.

Cees G. M. Snoek, H. Steven Scholte, Kandan Ramakrishnan, 2016 .

Characterizing the temporal dynamics of object recognition by deep neural networks : role of depth

Arnold W. M. Smeulders, Iris I. A. Groen, Sennay Ghebreab, 2017, bioRxiv.

Visual dictionaries as intermediate features in the human brain

Arnold W. M. Smeulders, Iris I. A. Groen, Sennay Ghebreab, 2015, Front. Comput. Neurosci..

Learning Domain-Specific Feature Descriptors for Document Images

Evgeniy Bart, Kandan Ramakrishnan, 2012, 2012 10th IAPR International Workshop on Document Analysis Systems.

A Large Scale Video Dataset for Event Recognition

Bolei Zhou, Aude Oliva, Carl Vondrick, 2018, Journal of Vision.

Moments in Time Dataset: One Million Videos for Event Understanding

Bolei Zhou, Lisa M. Brown, Quanfu Fan, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A cognitively-aligned representational space for DNNs

Yalda Mohsenzadeh, Aude Oliva, Mathew Monfort, 2019, Journal of Vision.

Examining Interpretable Feature Relationships in Deep Networks for Action recognition

Aude Oliva, Dan Gutfreund, Rogerio S. Feris, 2019 .

Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding

Quanfu Fan, Aude Oliva, Dan Gutfreund, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition

Quanfu Fan, Chun-Fu Chen, Aude Oliva, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search

Chun-Fu Chen, Michele Merler, Minsik Cho, 2021, AAAI.