no code implementations • 3 Apr 2022 • Qian Long, Kaushik Das, Poul Sørensen
In this paper, a novel hierarchical FC approach is proposed to allow HPPs to provide three types of FCSs, namely fast frequency response (FFR), frequency containment response (FCR) and frequency restoration response (FRR).
no code implementations • SEMEVAL 2020 • Arup Baruah, Kaushik Das, Ferdous Barbhuiya, Kuntal Dey
This architecture utilizes both textual and visual information present in a meme.
no code implementations • SEMEVAL 2020 • Arup Baruah, Kaushik Das, Ferdous Barbhuiya, Kuntal Dey
In this paper, we present the results that the team IIITG-ADBU (codalab username {`}abaruah{'}) obtained in the SentiMix task (Task 9) of the International Workshop on Semantic Evaluation 2020 (SemEval 2020).
no code implementations • SEMEVAL 2020 • Arup Baruah, Kaushik Das, Ferdous Barbhuiya, Kuntal Dey
The BiLSTM classifier obtained macro F1 score of 0. 57565 for subtask C. The paper also performs an analysis of the errors made by our classifiers.
no code implementations • WS 2020 • Arup Baruah, Kaushik Das, Ferdous Barbhuiya, Kuntal Dey
It was found that including the last utterance in the dialogue along with the response improved the performance of the classifier for the Twitter data set.
1 code implementation • LREC 2020 • Arup Baruah, Kaushik Das, Ferdous Barbhuiya, Kuntal Dey
In our study, we used English BERT (En-BERT), RoBERTa, DistilRoBERTa, and SVM based classifiers for English language.
Aggression Identification Misogynistic Aggression Identification
no code implementations • 27 Mar 2020 • Sarthak J. Shetty, Rahul Ravichandran, Lima Agnel Tony, N. Sai Abhinay, Kaushik Das, Debasish Ghose
The coordinates of the survivor and their heading is reported by an on-ground observer to the UAV to generate a weighted map of the surroundings for exploration.
Robotics Systems and Control Systems and Control
no code implementations • 27 Nov 2018 • Madhu Babu V, Swagat Kumar, Anima Majumder, Kaushik Das
In this paper, we provide an improved version of UnDEMoN model for depth and ego motion estimation from monocular images.
no code implementations • 27 Aug 2018 • Madhu Babu V, Anima Majumder, Kaushik Das, Swagat Kumar
The proposed network is trained using unlabeled monocular stereo image pairs and is shown to provide superior performance in depth and ego-motion estimation compared to the existing state-of-the-art.