62 citations · 245 across the 42 of their papers we have counts for
8 papers · 1 filter
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization
Suhas Lohit, Rushil Anirudh, Pavan Turaga
Motion capture (mocap) and time-of-flight based sensing of human actions are becoming increasingly popular modalities to perform robust activity analysis. Applications range from a…
Role of Orthogonality Constraints in Improving Properties of Deep Networks for Image Classification
Hongjun Choi, Anirudh Som, Pavan Turaga
Standard deep learning models that employ the categorical cross-entropy loss are known to perform well at image classification tasks. However, many standard models thus obtained of…
Generative Patch Priors for Practical Compressive Image Recovery
Rushil Anirudh, Suhas Lohit, Pavan Turaga
In this paper, we propose the generative patch prior (GPP) that defines a generative prior for compressive image recovery, based on patch-manifold models. Unlike learned, image-lev…
GraCIAS: Grassmannian of Corrupted Images for Adversarial Security
Ankita Shukla, Pavan Turaga, Saket Anand
Input transformation based defense strategies fall short in defending against strong adversarial attacks. Some successful defenses adopt approaches that either increase the randomn…
Unsupervised Pre-trained Models from Healthy ADLs Improve Parkinson's Disease Classification of Gait Patterns
Anirudh Som, Narayanan Krishnamurthi, Matthew Buman +1
Application and use of deep learning algorithms for different healthcare applications is gaining interest at a steady pace. However, use of such algorithms can prove to be challeng…
Topological Descriptors for Parkinson's Disease Classification and Regression Analysis
Afra Nawar, Farhan Rahman, Narayanan Krishnamurthi +2
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper,…
AMC-Loss: Angular Margin Contrastive Loss for Improved Explainability in Image Classification
Hongjun Choi, Anirudh Som, Pavan Turaga
Deep-learning architectures for classification problems involve the cross-entropy loss sometimes assisted with auxiliary loss functions like center loss, contrastive loss and tripl…
Halluci-Net: Scene Completion by Exploiting Object Co-occurrence Relationships
Kuldeep Kulkarni, Tejas Gokhale, Rajhans Singh +2
Recently, there has been substantial progress in image synthesis from semantic labelmaps. However, methods used for this task assume the availability of complete and unambiguous la…