Search Results for author: Amir Hussain

Found 54 papers, 5 papers with code

Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation

no code implementations13 Dec 2022 Chaolong Yang, Yuyao Yan, Weiguang Zhao, Jianan Ye, Xi Yang, Amir Hussain, Kaizhu Huang

On the one hand, the unidirectional projection enforces our model focused more on the core task, i. e., 3D segmentation; on the other hand, unlocking the bidirectional to unidirectional projection enables a deeper cross-domain semantic alignment and enjoys the flexibility to fuse better and complicated features from very different spaces.

3D Semantic Segmentation Scene Understanding

Audio-Visual Speech Enhancement and Separation by Leveraging Multi-Modal Self-Supervised Embeddings

no code implementations31 Oct 2022 I-Chun Chern, Kuo-Hsuan Hung, Yi-Ting Chen, Tassadaq Hussain, Mandar Gogate, Amir Hussain, Yu Tsao, Jen-Cheng Hou

In summary, our results confirm the effectiveness of our proposed model for the AVSS task with proper fine-tuning strategies, demonstrating that multi-modal self-supervised embeddings obtained from AV-HUBERT can be generalized to audio-visual regression tasks.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +6

A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids

no code implementations24 Oct 2022 Abhijeet Bishnu, Ankit Gupta, Mandar Gogate, Kia Dashtipour, Ahsan Adeel, Amir Hussain, Mathini Sellathurai, Tharmalingam Ratnarajah

In this paper, we design a first of its kind transceiver (PHY layer) prototype for cloud-based audio-visual (AV) speech enhancement (SE) complying with high data rate and low latency requirements of future multimodal hearing assistive technology.

Lip Reading Speech Enhancement

Canonical Cortical Graph Neural Networks and its Application for Speech Enhancement in Audio-Visual Hearing Aids

no code implementations6 Jun 2022 Leandro A. Passos, João Paulo Papa, Amir Hussain, Ahsan Adeel

Despite the recent success of machine learning algorithms, most models face drawbacks when considering more complex tasks requiring interaction between different sources, such as multimodal input data and logical time sequences.

BIG-bench Machine Learning Speech Enhancement

A Novel Speech Intelligibility Enhancement Model based on CanonicalCorrelation and Deep Learning

no code implementations11 Feb 2022 Tassadaq Hussain, Muhammad Diyan, Mandar Gogate, Kia Dashtipour, Ahsan Adeel, Yu Tsao, Amir Hussain

Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are often trained to minimise the feature distance between noise-free speech and enhanced speech signals.

Speech Enhancement

Design of Flexible Meander Line Antenna for Healthcare for Wireless Medical Body Area Networks

no code implementations8 Feb 2022 Shahid M Ali, Cheab Sovuthy, Sima Noghanian, Qammer H. Abbasi, Tatjana Asenova, Peter Derleth, Alex Casson, Tughrul Arslan, Amir Hussain

The MMA design shows a bandwidth of up to 1282. 4 (450. 5) MHz and provides gains of 3. 03 (4. 85) dBi in the lower and upper operating bands, respectively, showing omnidirectional radiation patterns in free space.

A Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning for Hearing-Assistive Technologies

no code implementations8 Feb 2022 Tassadaq Hussain, Muhammad Diyan, Mandar Gogate, Kia Dashtipour, Ahsan Adeel, Yu Tsao, Amir Hussain

Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are generally trained to minimise the distance between clean and enhanced speech features.

Speech Enhancement

A Novel Temporal Attentive-Pooling based Convolutional Recurrent Architecture for Acoustic Signal Enhancement

no code implementations24 Jan 2022 Tassadaq Hussain, Wei-Chien Wang, Mandar Gogate, Kia Dashtipour, Yu Tsao, Xugang Lu, Adeel Ahsan, Amir Hussain

To address this problem, we propose to integrate a novel temporal attentive-pooling (TAP) mechanism into a conventional convolutional recurrent neural network, termed as TAP-CRNN.

Towards Robust Real-time Audio-Visual Speech Enhancement

no code implementations16 Dec 2021 Mandar Gogate, Kia Dashtipour, Amir Hussain

The human brain contextually exploits heterogeneous sensory information to efficiently perform cognitive tasks including vision and hearing.

Speech Enhancement

Towards Intelligibility-Oriented Audio-Visual Speech Enhancement

1 code implementation18 Nov 2021 Tassadaq Hussain, Mandar Gogate, Kia Dashtipour, Amir Hussain

To the best of our knowledge, this is the first work that exploits the integration of AV modalities with an I-O based loss function for SE.

Speech Enhancement

Cloud based Scalable Object Recognition from Video Streams using Orientation Fusion and Convolutional Neural Networks

no code implementations19 Jun 2021 Muhammad Usman Yaseen, Ashiq Anjum, Giancarlo Fortino, Antonio Liotta, Amir Hussain

Herein we demonstrate how a feature-fusion strategy of the orientation components leads to further improving visual recognition accuracy to 97\%.

Object Recognition

FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning

no code implementations29 Apr 2021 Indro Spinelli, Simone Scardapane, Amir Hussain, Aurelio Uncini

Furthermore, to better evaluate the gains, we propose a new dyadic group definition to measure the bias of a link prediction task when paired with group-based fairness metrics.

Fairness Graph Representation Learning +1

A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling

no code implementations19 Apr 2021 Danilo Comminiello, Alireza Nezamdoust, Simone Scardapane, Michele Scarpiniti, Amir Hussain, Aurelio Uncini

In order to make this class of functional link adaptive filters (FLAFs) efficient, we propose low-complexity expansions and frequency-domain adaptation of the parameters.

Acoustic echo cancellation Domain Adaptation

Learning Polar Encodings for Arbitrary-Oriented Ship Detection in SAR Images

no code implementations24 Mar 2021 Yishan He, Fei Gao, Jun Wang, Amir Hussain, Erfu Yang, Huiyu Zhou

In this paper, in order to solve the boundary discontinuity problem in OBB regression, we propose to detect SAR ships by learning polar encodings.


A novel multimodal fusion network based on a joint coding model for lane line segmentation

no code implementations20 Mar 2021 Zhenhong Zou, Xinyu Zhang, Huaping Liu, Zhiwei Li, Amir Hussain, Jun Li

There has recently been growing interest in utilizing multimodal sensors to achieve robust lane line segmentation.

Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection

no code implementations16 Mar 2021 Chenwei Cui, Liangfu Lu, Zhiyuan Tan, Amir Hussain

The framework utilizes Conceptual Text Regions (CTRs), which is a class of cognition-based tools inheriting good mathematical properties, allowing for sophisticated label design.

Scene Text Detection

Persuasive Dialogue Understanding: the Baselines and Negative Results

no code implementations19 Nov 2020 Hui Chen, Deepanway Ghosal, Navonil Majumder, Amir Hussain, Soujanya Poria

Persuasion aims at forming one's opinion and action via a series of persuasive messages containing persuader's strategies.

Dialogue Understanding Intent Recognition +5

Discriminative Dictionary Design for Action Classification in Still Images and Videos

no code implementations20 May 2020 Abhinaba Roy, Biplab Banerjee, Amir Hussain, Soujanya Poria

Specifically, we pose the selection of potent local descriptors as filtering based feature selection problem which ranks the local features per category based on a novel measure of distinctiveness.

Action Classification Action Recognition +1

Improving Aspect-Level Sentiment Analysis with Aspect Extraction

no code implementations3 May 2020 Navonil Majumder, Rishabh Bhardwaj, Soujanya Poria, Amir Zadeh, Alexander Gelbukh, Amir Hussain, Louis-Philippe Morency

Aspect-based sentiment analysis (ABSA), a popular research area in NLP has two distinct parts -- aspect extraction (AE) and labeling the aspects with sentiment polarity (ALSA).

Aspect Extraction Word Embeddings

Deep Learning in Mining Biological Data

no code implementations28 Feb 2020 Mufti Mahmud, M. Shamim Kaiser, Amir Hussain

Highlighting the role of DL in recognizing patterns in biological data, this article provides - applications of DL to biological sequences, images, and signals data; overview of open access sources of these data; description of open source DL tools applicable on these data; and comparison of these tools from qualitative and quantitative perspectives.

Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations

no code implementations19 Feb 2020 Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera

Using these taxonomies we review more than three hundred publications dealing with nature-inspired and bio-inspired algorithms, and proposals falling within each of these categories are examined, leading to a critical summary of design trends and similarities between them, and the identification of the most similar classical algorithm for each reviewed paper.

AV Speech Enhancement Challenge using a Real Noisy Corpus

no code implementations30 Sep 2019 Mandar Gogate, Ahsan Adeel, Kia Dashtipour, Peter Derleth, Amir Hussain

This paper presents, a first of its kind, audio-visual (AV) speech enhacement challenge in real-noisy settings.

Speech Enhancement

A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks

no code implementations30 Sep 2019 Kia Dashtipour, Mandar Gogate, Jingpeng Li, Fengling Jiang, Bin Kong, Amir Hussain

When no pattern is triggered, the framework switches to its subsymbolic counterpart and leverages deep neural networks (DNN) to perform the classification.

Persian Sentiment Analysis

CochleaNet: A Robust Language-independent Audio-Visual Model for Speech Enhancement

no code implementations23 Sep 2019 Mandar Gogate, Kia Dashtipour, Ahsan Adeel, Amir Hussain

In addition, our work challenges a popular belief that a scarcity of multi-language large vocabulary AV corpus and wide variety of noises is a major bottleneck to build a robust language, speaker and noise independent SE systems.

Speech Enhancement

Attributes Guided Feature Learning for Vehicle Re-identification

no code implementations22 May 2019 Hongchao Li, Xianmin Lin, Aihua Zheng, Chenglong Li, Bin Luo, Ran He, Amir Hussain

In particular, our network is end-to-end trained and contains three subnetworks of deep features embedded by the corresponding attributes (i. e., camera view, vehicle type and vehicle color).

Vehicle Re-Identification


no code implementations ICLR 2019 Shufei Zhang, Kai-Zhu Huang, Rui Zhang, Amir Hussain

In this paper, we propose a generalized framework that addresses the learning problem of adversarial examples with Riemannian geometry.

Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments

no code implementations28 Aug 2018 Ahsan Adeel, Mandar Gogate, Amir Hussain

In this paper, we introduce a novel contextual AV switching component that contextually exploits AV cues with respect to different operating conditions to estimate clean audio, without requiring any SNR estimation.

Lip Reading Speech Enhancement

Saliency Detection via Bidirectional Absorbing Markov Chain

no code implementations25 Aug 2018 Fengling Jiang, Bin Kong, Ahsan Adeel, Yun Xiao, Amir Hussain

Simultaneously, foreground prior as the virtual absorbing nodes is used to calculate the absorption time and obtain the background possibility.

Saliency Detection Superpixels

SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis

no code implementations15 Aug 2018 Imane Guellil, Ahsan Adeel, Faical Azouaou, Amir Hussain

In this paper, we present a novel approach to automatically construct an annotated sentiment corpus for Algerian dialect (a Maghrebi Arabic dialect).

Sentiment Analysis Transliteration

DNN driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation

no code implementations31 Jul 2018 Mandar Gogate, Ahsan Adeel, Ricard Marxer, Jon Barker, Amir Hussain

The process of selective attention in the brain is known to contextually exploit the available audio and visual cues to better focus on target speaker while filtering out other noises.

Speech Separation

An Enhanced Binary Particle-Swarm Optimization (E-BPSO) Algorithm for Service Placement in Hybrid Cloud Platforms

no code implementations10 Jun 2018 Wissem Abbes, Zied Kechaou, Amir Hussain, Abdulrahman M. Qahtani, Omar Aimutiry, Habib Dhahri, Adel M. ALIMI

Nowadays, hybrid cloud platforms stand as an attractive solution for organizations intending to implement combined private and public cloud applications, in order to meet their profitability requirements.

Complex-valued Neural Networks with Non-parametric Activation Functions

2 code implementations22 Feb 2018 Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini

Complex-valued neural networks (CVNNs) are a powerful modeling tool for domains where data can be naturally interpreted in terms of complex numbers.

A Brain-Inspired Trust Management Model to Assure Security in a Cloud based IoT Framework for Neuroscience Applications

no code implementations11 Jan 2018 Mufti Mahmud, M. Shamim Kaiser, M. Mostafizur Rahman, M. Arifur Rahman, Antesar Shabut, Shamim Al-Mamun, Amir Hussain

To ensure secure and reliable data communication between end-to-end (E2E) devices supported by current IoT and cloud infrastructure, trust management is needed at the IoT and user ends.


Applications of Deep Learning and Reinforcement Learning to Biological Data

no code implementations10 Nov 2017 Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, Stefano Vassanelli

Rapid advances of hardware-based technologies during the past decades have opened up new possibilities for Life scientists to gather multimodal data in various application domains (e. g., Omics, Bioimaging, Medical Imaging, and [Brain/Body]-Machine Interfaces), thus generating novel opportunities for development of dedicated data intensive machine learning techniques.

reinforcement-learning Reinforcement Learning (RL)

Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges

no code implementations19 Sep 2017 Muhammad Usama, Junaid Qadir, Aunn Raza, Hunain Arif, Kok-Lim Alvin Yau, Yehia Elkhatib, Amir Hussain, Ala Al-Fuqaha

We provide a comprehensive survey highlighting the recent advancements in unsupervised learning techniques and describe their applications for various learning tasks in the context of networking.

Anomaly Detection BIG-bench Machine Learning +5

A novel agent-based simulation framework for sensing in complex adaptive environments

no code implementations19 Aug 2017 Muaz A. Niazi, Amir Hussain

In this paper we present a novel Formal Agent-Based Simulation framework (FABS).

Agent-based computing from multi-agent systems to agent-based Models: a visual survey

no code implementations19 Aug 2017 Muaz A. Niazi, Amir Hussain

Agent-Based Computing is a diverse research domain concerned with the building of intelligent software based on the concept of "agents".

Verification & Validation of Agent Based Simulations using the VOMAS (Virtual Overlay Multi-agent System) approach

no code implementations8 Aug 2017 Muaz A. Niazi, Amir Hussain, Mario Kolberg

Our technique, which allows for the validation of agent based simulations uses VOMAS: a Virtual Overlay Multi-agent System.

Agent based Tools for Modeling and Simulation of Self-Organization in Peer-to-Peer, Ad-Hoc and other Complex Networks

no code implementations4 Aug 2017 Muaz A. Niazi, Amir Hussain

Agent-based modeling and simulation tools provide a mature platform for development of complex simulations.

Benchmarking Multimodal Sentiment Analysis

no code implementations29 Jul 2017 Erik Cambria, Devamanyu Hazarika, Soujanya Poria, Amir Hussain, R. B. V. Subramaanyam

We propose a framework for multimodal sentiment analysis and emotion recognition using convolutional neural network-based feature extraction from text and visual modalities.

Benchmarking Emotion Recognition +1

Group Sparse Regularization for Deep Neural Networks

1 code implementation2 Jul 2016 Simone Scardapane, Danilo Comminiello, Amir Hussain, Aurelio Uncini

In this paper, we consider the joint task of simultaneously optimizing (i) the weights of a deep neural network, (ii) the number of neurons for each hidden layer, and (iii) the subset of active input features (i. e., feature selection).

Handwritten Digit Recognition

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