Search Results for author:
Found 9 papers, 1 papers with code
A Deeper Insight into the UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation
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.
UnDEMoN 2.0: Improved Depth and Ego Motion Estimation through Deep Image Sampling
In this paper, we provide an improved version of UnDEMoN model for depth and ego motion estimation from monocular images.
Implementation of Survivor Detection Strategies Using Drones
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
Aggression Identification in English, Hindi and Bangla Text using BERT, RoBERTa and SVM
In our study, we used English BERT (En-BERT), RoBERTa, DistilRoBERTa, and SVM based classifiers for English language.
Aggression Identification
Misogynistic Aggression Identification
Context-Aware Sarcasm Detection Using BERT
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.
IIITG-ADBU at SemEval-2020 Task 12: Comparison of BERT and BiLSTM in Detecting Offensive Language
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.
IIITG-ADBU at SemEval-2020 Task 8: A Multimodal Approach to Detect Offensive, Sarcastic and Humorous Memes
This architecture utilizes both textual and visual information present in a meme.
IIITG-ADBU at SemEval-2020 Task 9: SVM for Sentiment Analysis of English-Hindi Code-Mixed Text
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).
Hierarchical Frequency Control of Hybrid Power Plants Using Frequency Response Observer
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).
