Search Results for author:
Found 21 papers, 4 papers with code
Modelling Temporal Information Using Discrete Fourier Transform for Recognizing Emotions in User-generated Videos
By this way, static image features extracted from a pre-trained deep CNN and temporal information represented by DFT features are jointly considered for video emotion recognition.
Modelling Temporal Information Using Discrete Fourier Transform for Video Classification
In this way, static image features extracted from a pre-trained deep CNN and temporal information represented by DFT features are jointly considered for video classification.
Dual Pattern Learning Networks by Empirical Dual Prediction Risk Minimization
This architecture forces the network to learn discriminative class-specific features by analyzing and comparing two input images.
Suggestion Mining from Online Reviews using ULMFiT
In this paper we present our approach and the system description for Sub Task A of SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums.
Identifying Offensive Posts and Targeted Offense from Twitter
In this paper we present our approach and the system description for Sub-task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Media.
Dialogue Act Classification in Group Chats with DAG-LSTMs
In this paper, we introduce a new model architecture, directed-acyclic-graph LSTM (DAG-LSTM) for DA classification.
Keyphrase Generation for Scientific Articles using GANs
In this paper, we present a keyphrase generation approach using conditional Generative Adversarial Networks (GAN).
Keyphrase Extraction from Scholarly Articles as Sequence Labeling using Contextualized Embeddings
In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where the words in the input text are represented using deep contextualized embeddings.
An Annotated Dataset of Discourse Modes in Hindi Stories
In this paper, we present a new corpus consisting of sentences from Hindi short stories annotated for five different discourse modes argumentative, narrative, descriptive, dialogic and informative.
MIDAS at SemEval-2020 Task 10: Emphasis Selection using Label Distribution Learning and Contextual Embeddings
This paper presents our submission to the SemEval 2020 - Task 10 on emphasis selection in written text.
Two-Step Classification using Recasted Data for Low Resource Settings
We further improve the performance by using a joint-objective for classification and textual entailment.
Towards Counteracting Adversarial Perturbations to Resist Adversarial Examples
We validate the proposed method on CIFAR-10 and CIFAR-100.
SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolutional Networks
We show that applying stochastic scaling at the gradient level is complementary to that applied at the feature level to improve the overall performance.
Improving Transformation-based Defenses against Adversarial Examples with First-order Perturbations
Based on this observation, we propose a method for counteracting adversarial perturbations to improve adversarial robustness.
An Efficient Multitask Neural Network for Face Alignment, Head Pose Estimation and Face Tracking
Moreover, we generate a cheap heatmap based on the face alignment result and fuse it with features to improve the performance of the other two tasks.
Ranked #28 on
Face Alignment
on WFLW
On the Use of Context for Predicting Citation Worthiness of Sentences in Scholarly Articles
In this paper, we study the importance of context in predicting the citation worthiness of sentences in scholarly articles.
Multimodal Hyperspectral Image Classification via Interconnected Fusion
More specifically, they overlook the contextual information across modalities of HSI and LiDAR and the intra-modality characteristics of LiDAR.
Vital Sign Monitoring in Dynamic Environment via mmWave Radar and Camera Fusion
Contact-free vital sign monitoring, which uses wireless signals for recognizing human vital signs (i. e, breath and heartbeat), is an attractive solution to health and security.
Neighbour-level Message Interaction Encoding for Improved Representation Learning on Graphs
To address this issue, we propose a neighbour-level message interaction information encoding method for improving graph representation learning.
RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional Networks
Intuitively, we can expect the generated embeddings become smooth asymptotically layerwisely, that is each layer of graph convolution generates a smoothed version of embeddings as compared to that generated by the previous layer.
A Preliminary Exploration of GANs for Keyphrase Generation
We observed that our model achieves state-of-the-art performance in the generation of abstractive keyphrases and is comparable to the best performing extractive techniques.
