4 citations · 5 across the 9 of their papers we have counts for
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SAU: Smooth activation function using convolution with approximate identities
Koushik Biswas, Sandeep Kumar, Shilpak Banerjee +1
Well-known activation functions like ReLU or Leaky ReLU are non-differentiable at the origin. Over the years, many smooth approximations of ReLU have been proposed using various sm…
ErfAct and Pserf: Non-monotonic Smooth Trainable Activation Functions
Koushik Biswas, Sandeep Kumar, Shilpak Banerjee +1
An activation function is a crucial component of a neural network that introduces non-linearity in the network. The state-of-the-art performance of a neural network depends also on…
Tropical cyclone intensity estimations over the Indian ocean using Machine Learning
Koushik Biswas, Sandeep Kumar, Ashish Kumar Pandey
Tropical cyclones are one of the most powerful and destructive natural phenomena on earth. Tropical storms and heavy rains can cause floods, which lead to human lives and economic…
Intensity Prediction of Tropical Cyclones using Long Short-Term Memory Network
Koushik Biswas, Sandeep Kumar, Ashish Kumar Pandey
Tropical cyclones can be of varied intensity and cause a huge loss of lives and property if the intensity is high enough. Therefore, the prediction of the intensity of tropical cyc…
Prediction of Landfall Intensity, Location, and Time of a Tropical Cyclone
Sandeep Kumar, Koushik Biswas, Ashish Kumar Pandey
The prediction of the intensity, location and time of the landfall of a tropical cyclone well advance in time and with high accuracy can reduce human and material loss immensely. I…
Predicting Landfall's Location and Time of a Tropical Cyclone Using Reanalysis Data
Sandeep Kumar, Koushik Biswas, Ashish Kumar Pandey
Landfall of a tropical cyclone is the event when it moves over the land after crossing the coast of the ocean. It is important to know the characteristics of the landfall in terms…