98 citations · 348 across the 22 of their papers we have counts for
24 papers
Resolving the Decreased Rank Attack in RPL's IoT Networks
B. Ghaleb, A. Al-Dubai, A. Hussain +3
The Routing Protocol for Low power and Lossy networks (RPL) has been developed by the Internet Engineering Task Force (IETF) standardization body to serve as a part of the 6LoWPAN…
WikiDes: A Wikipedia-Based Dataset for Generating Short Descriptions from Paragraphs
Hoang Thang Ta, Abu Bakar Siddiqur Rahman, Navonil Majumder +5
As free online encyclopedias with massive volumes of content, Wikipedia and Wikidata are key to many Natural Language Processing (NLP) tasks, such as information retrieval, knowled…
Towards Simple and Accurate Human Pose Estimation with Stair Network
Chenru Jiang, Kaizhu Huang, Shufei Zhang +3
In this paper, we focus on tackling the precise keypoint coordinates regression task. Most existing approaches adopt complicated networks with a large number of parameters, leading…
A Novel Temporal Attentive-Pooling based Convolutional Recurrent Architecture for Acoustic Signal Enhancement
Tassadaq Hussain, Wei-Chien Wang, Mandar Gogate +5
In acoustic signal processing, the target signals usually carry semantic information, which is encoded in a hierarchal structure of short and long-term contexts. However, the backg…
Cloud based Scalable Object Recognition from Video Streams using Orientation Fusion and Convolutional Neural Networks
Muhammad Usman Yaseen, Ashiq Anjum, Giancarlo Fortino +2
Object recognition from live video streams comes with numerous challenges such as the variation in illumination conditions and poses. Convolutional neural networks (CNNs) have been…
A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling
Danilo Comminiello, Alireza Nezamdoust, Simone Scardapane +3
Nonlinear models are known to provide excellent performance in real-world applications that often operate in non-ideal conditions. However, such applications often require online p…
Learning Polar Encodings for Arbitrary-Oriented Ship Detection in SAR Images
Yishan He, Fei Gao, Jun Wang +3
Common horizontal bounding box (HBB)-based methods are not capable of accurately locating slender ship targets with arbitrary orientations in synthetic aperture radar (SAR) images.…
A novel multimodal fusion network based on a joint coding model for lane line segmentation
Zhenhong Zou, Xinyu Zhang, Huaping Liu +3
There has recently been growing interest in utilizing multimodal sensors to achieve robust lane line segmentation. In this paper, we introduce a novel multimodal fusion architectur…
Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection
Chenwei Cui, Liangfu Lu, Zhiyuan Tan +1
Segmentation-based methods are widely used for scene text detection due to their superiority in describing arbitrary-shaped text instances. However, two major problems still exist:…
A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis
Kia Dashtipour, Mandar Gogate, Erik Cambria +1
Most recent works on sentiment analysis have exploited the text modality. However, millions of hours of video recordings posted on social media platforms everyday hold vital unstru…
Persuasive Dialogue Understanding: the Baselines and Negative Results
Hui Chen, Deepanway Ghosal, Navonil Majumder +2
Persuasion aims at forming one's opinion and action via a series of persuasive messages containing persuader's strategies. Due to its potential application in persuasive dialogue s…
Deep Learning in Mining Biological Data
Mufti Mahmud, M Shamim Kaiser, Amir Hussain
Recent technological advancements in data acquisition tools allowed life scientists to acquire multimodal data from different biological application domains. Broadly categorized in…
AV Speech Enhancement Challenge using a Real Noisy Corpus
Mandar Gogate, Ahsan Adeel, Kia Dashtipour +2
This paper presents, a first of its kind, audio-visual (AV) speech enhacement challenge in real-noisy settings. A detailed description of the AV challenge, a novel real noisy AV co…
A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks
Kia Dashtipour, Mandar Gogate, Jingpeng Li +3
Social media hold valuable, vast and unstructured information on public opinion that can be utilized to improve products and services. The automatic analysis of such data, however,…
CochleaNet: A Robust Language-independent Audio-Visual Model for Speech Enhancement
Mandar Gogate, Kia Dashtipour, Ahsan Adeel +1
Noisy situations cause huge problems for suffers of hearing loss as hearing aids often make the signal more audible but do not always restore the intelligibility. In noisy settings…
Attributes Guided Feature Learning for Vehicle Re-identification
Hongchao Li, Xianmin Lin, Aihua Zheng +4
Vehicle Re-ID has recently attracted enthusiastic attention due to its potential applications in smart city and urban surveillance. However, it suffers from large intra-class varia…
Real-Time Lightweight Chaotic Encryption for 5G IoT Enabled Lip-Reading Driven Secure Hearing-Aid
Ahsan Adeel, Jawad Ahmad, Amir Hussain
Existing audio-only hearing-aids are known to perform poorly in noisy situations where overwhelming noise is present. Next-generation audio-visual (lip-reading driven) hearing-aids…
Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments
Ahsan Adeel, Mandar Gogate, Amir Hussain
Human speech processing is inherently multimodal, where visual cues (lip movements) help to better understand the speech in noise. Lip-reading driven speech enhancement significant…
DNN driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation
Mandar Gogate, Ahsan Adeel, Ricard Marxer +2
Human auditory cortex excels at selectively suppressing background noise to focus on a target speaker. The process of selective attention in the brain is known to contextually expl…
Lip-Reading Driven Deep Learning Approach for Speech Enhancement
Ahsan Adeel, Mandar Gogate, Amir Hussain +1
This paper proposes a novel lip-reading driven deep learning framework for speech enhancement. The proposed approach leverages the complementary strengths of both deep learning and…
Multimodal Sentiment Analysis: Addressing Key Issues and Setting up the Baselines
Soujanya Poria, Navonil Majumder, Devamanyu Hazarika +3
We compile baselines, along with dataset split, for multimodal sentiment analysis. In this paper, we explore three different deep-learning based architectures for multimodal sentim…
Complex-valued Neural Networks with Non-parametric Activation Functions
Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain +1
Complex-valued neural networks (CVNNs) are a powerful modeling tool for domains where data can be naturally interpreted in terms of complex numbers. However, several analytical pro…
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
Muhammad Usama, Junaid Qadir, Aunn Raza +5
While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently there has been…
A new recurrent neural network based predictive model for Faecal Calprotectin analysis: A retrospective study
Zeeshan Khawar Malik, Zain U. Hussain, Ziad Kobti +3
Faecal Calprotectin (FC) is a surrogate marker for intestinal inflammation, termed Inflammatory Bowel Disease (IBD), but not for cancer. In this retrospective study of 804 patients…