Search Results for author:
Found 41 papers, 5 papers with code
CLPLM: Character Level Pretrained Language Model for ExtractingSupport Phrases for Sentiment Labels
In this paper, we have designed a character-level pre-trained language model for extracting support phrases from tweets based on the sentiment label.
COPS: A Compact On-device Pipeline for real-time Smishing detection
Smartphones have become indispensable in our daily lives and can do almost everything, from communication to online shopping.
ML-based PBCH symbol detection and equalization for 5G Non-Terrestrial Networks
This paper delves into the application of Machine Learning (ML) techniques in the realm of 5G Non-Terrestrial Networks (5G-NTN), particularly focusing on symbol detection and equalization for the Physical Broadcast Channel (PBCH).
IRS Assisted MIMO Full Duplex: Rate Analysis and Beamforming Under Imperfect CSI
In this manuscript, we present a novel approach to jointly optimize active and passive beamforming in a multiple-input-multiple-output (MIMO) FD system assisted by an IRS for weighted sum rate (WSR) maximization.
Robust Beamforming for IRS Aided MIMO Full Duplex Systems
We also analyze the achievable WSR of an IRS-assisted FD with imperfect CSI, for which the lower and the upper bounds are derived.
An Embedded Auto-Calibrated Offset Current Compensation Technique for PPG/fNIRS System
A prototype of the system is built and tested for PPG signal recording.
SeLiNet: Sentiment enriched Lightweight Network for Emotion Recognition in Images
In this paper, we propose a sentiment-enriched lightweight network SeLiNet and an end-to-end on-device pipeline for contextual emotion recognition in images.
Optimization for truss design using Bayesian optimization
We rely on finite element analysis, which is a computationally costly design analysis tool for design evaluation.
LEAN: Light and Efficient Audio Classification Network
Over the past few years, audio classification task on large-scale dataset such as AudioSet has been an important research area.
Malaria detection using Deep Convolution Neural Network
The latest WHO report showed that the number of malaria cases climbed to 219 million last year, two million higher than last year.
Balanced Deep CCA for Bird Vocalization Detection
The key objective of this work is to learn useful embeddings associated with high performance in downstream event detection tasks when labeled data is scarce and the audio events of interest (songbird vocalizations) are sparse.
EmoSens: Emotion Recognition based on Sensor data analysis using LightGBM
Smart wearables have played an integral part in our day to day life.
LIP: Lightweight Intelligent Preprocessor for meaningful text-to-speech
In this work, we aim to introduce a lightweight intelligent preprocessor (LIP) that can enhance the readability of a message before being passed downstream to existing TTS systems.
Architectures and Synchronization Techniques for Distributed Satellite Systems: A Survey
This article also provides an extensive list of applications and examples of synchronization techniques for DSS in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position.
GGA-MLP: A Greedy Genetic Algorithm to Optimize Weights and Biases in Multilayer Perceptron
Various gradient-based optimization algorithms have been proposed by researchers in the past to generate an optimal set of weights and biases.
LEAPMood: Light and Efficient Architecture to Predict Mood with Genetic Algorithm driven Hyperparameter Tuning
LEAPMood consists of Emotion Recognition in Conversion (ERC) as the first building block followed by mood prediction using K-means clustering.
PrivPAS: A real time Privacy-Preserving AI System and applied ethics
This motivates us to work towards a solution to generate privacy-conscious cues for raising awareness in smartphone users of any sensitivity in their viewfinder content.
Adaptive Beam Search to Enhance On-device Abstractive Summarization
In this paper, we tackle this issue and for the first time, propose a novel Adaptive Beam Search to improve the quality of on-device abstractive summarization that can be applied to SMS, voice messages and can be extended to documents.
VoiceMoji: A Novel On-Device Pipeline for Seamless Emoji Insertion in Dictation
To the best of our knowledge, this is the first work that shows how to add emoji(s) in the transcribed text.
TweetBLM: A Hate Speech Dataset and Analysis of Black Lives Matter-related Microblogs on Twitter
Our dataset comprises 9165 manually annotated tweets that target the Black Lives Matter movement.
Coexistence of Communications and Cognitive MIMO Radar: Waveform Design and Prototype
New generation of radar systems will need to coexist with other radio frequency (RF) systems, anticipating their behavior and reacting appropriately to avoid interference.
Blockchain Technology: Introduction, Integration and Security Issues with IoT
This article elaborates on these two categories as well.
Cryptography and Security
SoftNER: Mining Knowledge Graphs From Cloud Incidents
We have deployed SoftNER at Microsoft, a major cloud service provider and have evaluated it on more than 2 months of cloud incidents.
On-Device Document Classification using multimodal features
For this task, we integrate an open-source library for Optical Character Recognition (OCR) and our novel model architecture in the pipeline.
A Remote Carrier Synchronization Technique for Coherent Distributed Remote Sensing Systems
Phase, frequency, and time synchronization are crucial requirements for many applications, such as multi-static remote sensing and communication systems.
CLPLM: Character Level Pretrained Language Model for Extracting Support Phrases for Sentiment Labels
In this paper, we have designed a character-level pre-trained language model for extracting support phrases from tweets based on the sentiment label.
Improving Neural Text Summarization using Knowledge Graphs
In this paper, we propose a method for extractive text summarization using auto-regressive transformers.
M2D: A Multi-modal Framework for Automatic Medical Diagnosis
In this paper, we present M2D: a multimodal deep learning framework for automatic medical condition diagnosis via transfer learning.
Biomedical Network Link Prediction using Neural Network Graph Embedding
In this paper, we aim at Graph embedding learning for automatic grasping of low-dimensional node representation on biomedical networks.
Towards Automatic Sentiment-based Topic Phrase Generation
For obtaining a comprehensive understanding and knowledge of customers’ expectations and demands, analysis of user-generated online product and service reviews is very important.
A Conglomerate of Multiple OCR Table Detection and Extraction
Information representation as tables are compact and concise method that eases searching, indexing, and storage requirements.
Interaction-Based Trajectory Prediction Over a Hybrid Traffic Graph
Behavior prediction of traffic actors is an essential component of any real-world self-driving system.
Neural Knowledge Extraction From Cloud Service Incidents
Prior work on incident management has been heavily focused on the challenges with incident triaging and de-duplication.
TweetBLM: A Hate Speech Dataset and Analysis of Black Lives Matter-related Microblogs on Twitter:
Our dataset is consists of 9165 manually annotated tweets that target the Black Lives Matter movement.
On- Device Information Extraction from Screenshots in form of tags
We propose a method to make mobile screenshots easily searchable.
MAME : Model-Agnostic Meta-Exploration
Meta-Reinforcement learning approaches aim to develop learning procedures that can adapt quickly to a distribution of tasks with the help of a few examples.
2-OGC: Open Gravitational-wave Catalog of binary mergers from analysis of public Advanced LIGO and Virgo data
We identify a population of 14 binary black hole mergers with $p_{\mathrm{astro}} > 0. 5$ along with the GW170817 binary neutron star merger.
High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology
GW170817: Stringent constraints on neutron-star radii from multimessenger observations and nuclear theory
The properties of neutron stars are determined by the nature of the matter that they contain.
High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology High Energy Physics - Phenomenology Nuclear Theory
Learning Transferable Cooperative Behavior in Multi-Agent Teams
While multi-agent interactions can be naturally modeled as a graph, the environment has traditionally been considered as a black box.
Learning Configuration Space Belief Model from Collision Checks for Motion Planning
Our aim is to reduce the expected number of collision checks by creating a belief model of the configuration space using results from collision tests.
Active Learning with Gaussian Processes for High Throughput Phenotyping
A looming question that must be solved before robotic plant phenotyping capabilities can have significant impact to crop improvement programs is scalability.
