12 citations · 19 across the 6 of their papers we have counts for
6 papers
WavePaint: Resource-efficient Token-mixer for Self-supervised Inpainting
Pranav Jeevan, Dharshan Sampath Kumar, Amit Sethi
Image inpainting, which refers to the synthesis of missing regions in an image, can help restore occluded or degraded areas and also serve as a precursor task for self-supervision.…
Shallow Water Bathymetry Survey using an Autonomous Surface Vehicle
Bibin Wilson, Anand Singh, Amit Sethi
Accurate and cost effective mapping of water bodies has an enormous significance for environmental understanding and navigation. However, the quantity and quality of information we…
Convolutional Xformers for Vision
Pranav Jeevan, Amit sethi
Vision transformers (ViTs) have found only limited practical use in processing images, in spite of their state-of-the-art accuracy on certain benchmarks. The reason for their limit…
Memory Efficient Adaptive Attention For Multiple Domain Learning
Himanshu Pradeep Aswani, Abhiraj Sunil Kanse, Shubhang Bhatnagar +1
Training CNNs from scratch on new domains typically demands large numbers of labeled images and computations, which is not suitable for low-power hardware. One way to reduce these…
Vision Xformers: Efficient Attention for Image Classification
Pranav Jeevan, Amit Sethi
Although transformers have become the neural architectures of choice for natural language processing, they require orders of magnitude more training data, GPU memory, and computati…
Activation Functions: Do They Represent A Trade-Off Between Modular Nature of Neural Networks And Task Performance
Himanshu Pradeep Aswani, Amit Sethi
Current research suggests that the key factors in designing neural network architectures involve choosing number of filters for every convolution layer, number of hidden neurons fo…