Author details
Author's Published Works
Author details
Showing 1-25 of 43 results
- Sort
Filter Results
Show
Sort By
Results
ENADL: Towards Performance Improvement of IoT Networks Using Deep Learning-Based Node Fault Prediction
Shraddha Tripathi;Faheem Nizar;Om Jee Pandey;Tushar Sandhan;Rajesh M. Hegde
IEEE Transactions on Reliability
Year: 2025 | Early Access Article |
The Internet of Things (IoT) has grown explosively with wireless technology integration. Several IoT applications require high data throughput, low data transmission latency, and high data gathering reliability. Since, the IoT network (IoTN) is generally dynamic and utilizes a multi-hop data transmission scheme for such applications, the throughput, latency, and network lifetime tend to degrade as...Show More
MalaNet: A Small World Inspired Neural Network for Automated Malaria Diagnosis
Shubham Dwivedi;Kartikeya Pandey;Kumar Shubham;Om Jee Pandey;Achyut Mani Tripathi;Tushar Sandhan;Rajesh M Hegde
IEEE Transactions on Artificial Intelligence
Year: 2025 | Early Access Article |
In this work, a novel neural network architecture called MalaNet is proposed for the detection and diagnosis of malaria, an infectious disease that poses a major global health challenge. The proposed neural network architecture is inspired by small-world network principles, which generally involve the introduction of new links. A small-world neural network is realized by establishing new connectio...Show More
DoA Estimation in RIS-Assisted Network via Element Sampling and Sparse Reconstruction
Shraddha Tripathi;Ahmet M. Elbir;Tushar Sandhan;Rajesh M. Hegde
2024 3rd International Conference on 6G Networking (6GNet)
Year: 2024 | Conference Paper |
This work addresses a direction-of-arrival (DoA) estimation problem in a reconfigurable intelligent surface (RIS)-assisted network scenario. The accurate DoA information enables precise tracking and positioning of users for navigation, surveillance, and wireless communications. A strong direct link between the access point (AP) and the user is essential for DoA estimation. However, when the direct...Show More
Automated Segmentation of Lesions Associated with Tinea Pedis Disease
2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2024 | Conference Paper |
Tinea pedis, commonly referred to as athlete’s foot, remains a prevalent dermatophytic infection affecting the feet. The use of AI-driven healthcare solutions has attracted a lot of attention lately, especially when it comes to the diagnosis and treatment of diseases. This research aims to enhance the current understanding and methods by introducing an automated segmentation technique designed to ...Show More
Comparative Analysis of Fractal and ArUco marker for Navigation and Landing of Drones
2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2024 | Conference Paper |
The detection and pose estimation of markers are increasingly crucial across various domains, including human-robot interaction, UAV navigation, robotic grasping, and underwater navigation and many more. This paper evaluates the robustness of two prominent fiducial markers ArUco and Fractal marker, under diverse environmental conditions. These conditions include static and dynamic platforms, varyi...Show More
Localization through RGB-D Camera for the Quad-rotor
Vidit Datt Prabhakar;Vijay Kumar Pandey;Anuj Kumar Sharma;Tushar Sandhan
2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2024 | Conference Paper |
This paper presents a thorough investigation into the implementation of a localization system using a RGB-D camera that prioritizes computational efficiency. The study focuses on utilizing the Oak D Pro depth camera, which includes an in-built Inertial Measurement Unit. Visual Odometry is used to estimate the camera pose which is lighter in computation than other algorithms like Simultaneous Local...Show More
Detection of Irregular Shapes Resembling Non-Uniform Gaps for UAV Navigation
2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2024 | Conference Paper |
This research paper presents a novel approach for the detection and segmentation of non-uniform gaps to facilitate safe autonomous navigation of UAVs (Unmanned Aerial Vehicles) using the YOLOv8 deep learning model. The methodology comprises three key stages: data collection, annotation, and model training using the YOLOv8 architecture. Initially, the model is trained on regular shapes images such ...Show More
Gait Pattern Recognition via Fusing Static and Dynamic Features in Single Stream Network
Isha Jain;Navya;Dharini Reddy;Vijay Kumar Pandey;Tushar Sandhan
2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2024 | Conference Paper |
Gait refers to the walking and motion characteristics of an individual. In this paper, we suggest a unique method for analyzing human gait patterns using static as well as dynamic features passing through the same convolutional neural network. Generally, the gaits are processed using contour detection and segmentation to perform time series analysis with extracted features. Furthermore, machine le...Show More
Anomalous Node Detection in Socially-Aware Mobile IoT Networks Using Q-Learning
2024 International Conference on Signal Processing and Communications (SPCOM)
Year: 2024 | Conference Paper |
Rapid growth in demand for Internet of Things (IoT) applications has driven advancements in network tech-nologies. Mobile IoT applications, including tracking, intelli-gent wearables, and autonomous vehicles, necessitate high data throughput, privacy, low-latency data transfer, and prolonged network lifetime. In every IoT application, many sensor devices collect data from physical objects and send...Show More
Scalable and Time-Efficient Bin-Picking for Unknown Objects in Dense Clutter
The task of fully automated picking of novel bin objects that are placed in a densely cluttered pile poses a significant challenge. It becomes even more challenging if the objects are of various shapes, sizes, colors, and textures. Generally, grasp planning for a given scene begins with sampling several grasp poses, which are then evaluated to determine the final grasp pose for the robot action. W...Show More
Bin-Picking of Novel Objects Through Category-Agnostic-Segmentation: RGB Matters
Prem Raj;Sachin Bhadang;Gaurav Chaudhary;Laxmidhar Behera;Tushar Sandhan
2023 Seventh IEEE International Conference on Robotic Computing (IRC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
This paper addresses category-agnostic instance segmentation for robotic manipulation, focusing on segmenting objects independent of their class to enable versatile applications like bin-picking in dynamic environments. Existing methods often lack generalizability and object-specific information, leading to grasp failures. We present a novel approach leveraging objectcentric instance segmentation ...Show More
Classroom Audio Analysis for Estimating Engagement of the Students
Hidangmayum Bebina Devi;Piyush Bhatia;Xiaohui Yuan;Prakash Duraisamy;Tushar Sandhan
2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)
Year: 2023 | Conference Paper |
We propose an innovative approach for accurately classifying classroom audio into monotonous and engaging categories using Mel frequency cepstral coefficients (MFCC) feature extraction, and Convolutional Neural Networks (CNN). By leveraging MFCC, our method effectively captures the spectral and temporal information of audio signals. A CNN architecture is employed to classify the audio, utilizing f...Show More
Small-World Inspired Neural Network (SW-NN) for an Effective and Accurate Diagnosis of Diabetes
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
As the use of artificial intelligence in medical diagnosis is growing, the need for enhanced efficacy is becoming paramount. By merging the robustness of neural networks with the distinctive attributes of small-world networks (SWN), the possibility arises for even greater levels of accuracy with maintaining good generalizability. This work presents a novel approach for diagnosing diabetes using a ...Show More
Enhancing Multi-Label Image Recognition through Class-Specific Residual Attention
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
Researchers in the field of computer vision encounter challenges like label sparsity, label dependency, imbalanced label distribution, and feature representation when trying to address the problem of label recognition inside a single image containing several labels. Class-specific residual attention (CSRA) aims to highlight discriminative areas connected to each label by recording attention maps s...Show More
Hierarchical Swin Transformers and Graph Convolutional Nets for Iris Antispoofing
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
Iris recognition is widely employed as a biometric authentication technique. It is valued for its high precision and user-friendliness. However, these systems are susceptible to spoofing attacks, wherein fraudulent irises or photographs of genuine irises are presented to deceive the system. To address this vulnerability, iris antispoofing techniques are utilized to differentiate between authentic ...Show More
Regularized Fusion of CNN with Transfer Learning for Facial Emotion Recognition
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Emotional states of a person are hard to predict accurately by machines. Facial emotion recognition (FER) has become one of the prominent areas of study, because of its various applications. The objective of this work is to enhance the accuracy of facial emotion recognition by employing regularization and fusion techniques when the profile view images, in addition to frontal view images, are consi...Show More
Dissecting the Convolutional Neural Networks via Activation Maps for agricultural rice grain quality prediction
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
There has been a meteoric rise in the application of AI during the past decade. Researchers are looking into using AI algorithms in almost every domain. AI algorithms are being used in modern agricultural research and practices for a variety of tasks, from quality control to increasing agricultural production. Using Deep Learning algorithms can be difficult because of their heuristic character. Cl...Show More
Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Handling the system’s nonlinearity is a challenging aspect for the controllers’ design. The four-wheel independent steering, four-wheel independent drive (4WIS4WID) electrical vehicle (EV) composes of a pneumatic tire, motors and suspension system, which all are nonlinear. The classical controller is not a suitable choice for a nonlinear system. An autonomous electric vehicle’s path-tracking contr...Show More
Regressing the Cyclones with CNN via Continuous Satellite Image Classification
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
In this work, tropical cyclone intensity estimation is approached as a continuous image classification problem, with gradual changes in the intensity values. The key objective of existing methods that approach cyclone intensity estimation as an image classification task is to generate accurate and differentiating representations of the cyclone images from different categories. These techniques do ...Show More
Convolutional Neural Networks for Image Emotion Recognition by fusing Differential and Supplementary Information
Shashank Rapolu;Aman Singh;Ayush Dhingra;Ajaz Hussain;Tushar Sandhan
2023 International Conference on Bio Signals, Images, and Instrumentation (ICBSII)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Emotions arise out of complex phenomena, which are believed to have a biological basis. Neuroscience research has demonstrated that emotions are related to distinct patterns of brain activity and the release of certain chemicals, such as hormones and neurotransmitters, into the bloodstream. Emotion recognition is used in many applications, such as advertising, social networking, and cinema. In thi...Show More
Statistical and Deep Convolutional Feature Fusion for Emotion Detection from Audio Signal
Durgesh Ameta;Vinay Gupta;Rohit Pilakkottil Sathian;Laxmidhar Behera;Tushar Sandhan
2023 International Conference on Bio Signals, Images, and Instrumentation (ICBSII)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Speech serves as a crucial mode of expression for individuals to articulate their thoughts and can offer valuable insight into their emotional state. Various research has been conducted to identify metrics that can be used to determine the emotional sentiment hidden in an audio signal. This paper presents an exploratory analysis of various audio features, including Chroma features, MFCCs, Spectral...Show More
Active Feedback using Riemannian Features for Motor Imagery Classification
Vinay Gupta;Rishi Mittal;Durgesh Ameta;Laxmidhar Behera;Tushar Sandhan
2023 International Conference on Bio Signals, Images, and Instrumentation (ICBSII)
Year: 2023 | Conference Paper |
Brain-Computer Interface (BCI) technologies employing electroencephalography (EEG) signals heavily depend on effective and accurate signal classification strategies. Researchers have extensively developed various machine learning (ML) algorithms. However, very little has been done to improve the user’s ability to elicit better brain patterns easily distinguishable across different stimuli. This pa...Show More
AI based Stability Prediction and Analysis of Human Respiratory System
2023 International Conference on Microwave, Optical, and Communication Engineering (ICMOCE)
Year: 2023 | Conference Paper |
The most important systems in the human body is the respiratory system (RS). To comprehend the various functions of the human respiratory system, including gas regulation, $CO_{2}$ and $O_{2}$ transit delays, congestive heart failure, Cheyne-Stokes respiration, apnea, mouth pressure, and airflow, a number of mathematical models are available in the literature. However, these models have been exami...Show More
IR-UWB radar based through-wall human detection with limited data via multi-hop residual CNN
2023 International Conference on Microwave, Optical, and Communication Engineering (ICMOCE)
Year: 2023 | Conference Paper |
Human detection from behind a wall is a modern problem that is now being studied. This has several potential applications including disaster relief, counter-terrorism efforts, and medical diagnosis. In general, radar data can be recorded, which can be used to get information about the real world. This must be turned into visuals that can be used to train a deep-learning model. We used data from a ...Show More
Improved Pneumonia Diagnosis of Radiological Images using Hybrid Loss with Conventional CNN
2023 International Conference on Microwave, Optical, and Communication Engineering (ICMOCE)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
A bacterial infection is the root cause of pneumonia, a lung condition. Early diagnosis is crucial for the success of the therapeutic process. Chest X-ray images typically allow a qualified radiologist to make the diagnosis. The visual observation of the disease is one thing that can make a diagnosis challenging, and it can also be misdiagnosed for other concealed diseases in chest X-ray images. A...Show More
IEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.