Research

At the moment, my interests broadly lie in the fields of computer vision, robot learning and deep reinforcement learning.

Publications

• How Useful is Image-Based Active Learning for Plant Organ Segmentation?
  S. Rawat, Akshay L Chandra, S.V. Desai, Vineeth N Balasubramanian, S. Ninomiya, W. Guo
  Plant Phenomics, 2022
  Paper Code Journal

• On Initial Pools for Deep Active Learning
  Akshay L Chandra^†, S.V. Desai^†, C. Devaguptapu^†, Vineeth N Balasubramanian
  Preregistration Workshop at NeurIPS 2020 (PMLR Volume 148)
  ^{† Equal Contribution}
  ArXiv Code Workshop

• Active Learning with Point Supervision for Cost-Effective Panicle Detection in Cereal Crops
  Akshay L Chandra, S.V. Desai, Vineeth N Balasubramanian, S. Ninomiya, W. Guo
  BioMed Central Plant Methods (BMC), 2020 [Impact Factor: 4.993]
  ArXiv Journal

• An Adaptive Supervision Framework for Active Learning in Object Detection
  Akshay L Chandra^†, S.V. Desai^†, W. Guo, S. Ninomiya, Vineeth N Balasubramanian
  British Machine Vision Conference (BMVC), 2019
  ^{† Equal Contribution}
  ArXiv Poster

• EasyRFP: An Easy to Use Edge Computing Toolkit for Real-Time Field Phenotyping
  Akshay L Chandra^†, S.V. Desai^†, M. Hirafuji, S. Ninomiya, V N Balasubramanian, W. Guo
  Extended Abstract at CVPPP & ECCV Academic Demonstrations, 2020
  ^{† Equal Contribution}
  Code Video

GitHub Projects

• WCSAC: Worst-Case Soft Actor-Critic for Safety-Constrained Reinforcement Learning
  A Pytorch toolkit, July 2022
  Abstract:
  A PyTorch implementation of WCSAC with consistent benchmarks and baselines on OpenAI’s Safety-Gym Environment.
  Code Paper Our Report

• Deep Active Learning Toolkit for Image Classification
  A PyTorch Toolkit, May 2021
  Abstract:
  A PyTorch toolkit with 8 popular deep active learning query methods which include DBAL, VAAL, Coreset, Ensemble Variation-Ratio and more. Our toolkit currently supports CIFAR10/100, MNIST, SVHN, Tiny Imagenet and Long-Tails versions of CIFAR10/100.
  Code

• Image & Bounding Box Annotation Slicer
  An Object Detection Data Transformer, April 2019
  Abstract:
  This easy-to-use library is a data transformer mainly useful in Object Detection tasks. It slices images and their bounding box annotations into smaller tiles, both into specific sizes and into any arbitrarynumber of equal parts. It can also resize them, both by specific sizes and by a resizing/scaling factor.
  Docs Code PyPI

• Mouse Cursor Control With Facial Movements
  An HCI Application, October 2018
  Abstract:
  This Human-Computer Interaction application in Python will allow you to control your mouse cursor with your facial movements, works with just your regular webcam. Its hands-free, no wearable hardware or sensors needed.
  Post Code Video

• Robust Morse Code Converter (Incomplete)
  A Fun Deep Learning Application, August 2018
  Abstract:
  This 4-in-1 application can convert Morse Code signalled in 4 different ways in real time. Namely, flashlight toggles, eye winking, hand gestures and mouse clicks.
  Code

• Selfie Filters Using Facial Landmarks
  A Fun Facial Keypoints Application, May 2018
  Abstract:
  This deep learning application in Python can put various sunglasses on a detected face (I am calling them ‘Selfie Filters’) by detecting the Facial Landmarks (15 unique points). These landmarks mark important areas of the face - the eyes, corners of the mouth, the nose, etc.
  Post Code Video

• Alphabet Recognition Through Gestures
  A Gesture Recognition Application, April 2018
  Abstract:
  This deep learning application in python recognizes alphabet through gestures captured real time on a webcam. The user is allowed to write the alphabet on the screen using an object-of-interest (a water bottle cap in this case).
  Post Code Video