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Found 26 papers, 5 papers with code
An Adaptive feature mode decomposition based on a novel health indicator for bearing fault diagnosis
Initially, the artificial hummingbird algorithm (AHA) is used to make the feature mode decomposition (FMD) adaptive by optimizing its parameter based on a newly developed health indicator (HI) i. e. sparsity impact measure index (SIMI).
Intelligent fault diagnosis of worm gearbox based on adaptive CNN using amended gorilla troop optimization with quantum gate mutation strategy
Therefore it becomes necessary to develop a robust fault diagnosis scheme for worm gearbox.
Optical Screening of Citrus Leaf Diseases Using Label-Free Spectroscopic Tools: A Review
Citrus diseases pose threats to citrus farming and result in economic losses worldwide.
Can LLMs Compute with Reasons?
Large language models (LLMs) often struggle with complex mathematical tasks, prone to "hallucinating" incorrect answers due to their reliance on statistical patterns.
Deep Generative Attacks and Countermeasures for Data-Driven Offline Signature Verification
Then, we attacked these baselines using the synthetic datasets.
Dictionary Attack on IMU-based Gait Authentication
We present a novel adversarial model for authentication systems that use gait patterns recorded by the inertial measurement unit (IMU) built into smartphones.
Quantitative analysis of collagen remodeling in pancreatic lesions using computationally translated collagen images derived from brightfield microscopy images
However, a technical approach that can perform a quantitative analysis of fibrillar collagen directly on standard slides stained with H&E can (i) discard the need for specialized and costly equipment or labels, (ii) further supplement the conventional histopathological insights and, (iii) potentially be integrated within the framework of standard histopathology workflow.
Synthesizing Human Gaze Feedback for Improved NLP Performance
Feedback can be either explicit (e. g. ranking used in training language models) or implicit (e. g. using human cognitive signals in the form of eyetracking).
iCTGAN--An Attack Mitigation Technique for Random-vector Attack on Accelerometer-based Gait Authentication Systems
A recent study showed that commonly (vanilla) studied implementations of accelerometer-based gait authentication systems ($v$ABGait) are susceptible to random-vector attack.
GANTouch: An Attack-Resilient Framework for Touch-based Continuous Authentication System
Zero-effort, Population, and Random-vector.
Sparse Image based Navigation Architecture to Mitigate the need of precise Localization in Mobile Robots
Traditional simultaneous localization and mapping (SLAM) methods focus on improvement in the robot's localization under environment and sensor uncertainty.
Attention-based Estimation and Prediction of Human Intent to augment Haptic Glove aided Control of Robotic Hand
The test-MSE in prediction of human intent is reported to yield ~ 97. 3 -98. 7% improvement of accuracy in comparison to LSTM-based benchmark
Defending Touch-based Continuous Authentication Systems from Active Adversaries Using Generative Adversarial Networks
Previous studies have demonstrated that commonly studied (vanilla) touch-based continuous authentication systems (V-TCAS) are susceptible to population attack.
Communication is the universal solvent: atreya bot -- an interactive bot for chemical scientists
In this paper, we introduce "Atreya", an interactive bot for chemistry enthusiasts, researchers, and students to study the ChEMBL database.
Blockchain based Privacy-Preserved Federated Learning for Medical Images: A Case Study of COVID-19 CT Scans
To solve this challenging task, we propose a blockchain-based federated learning framework that provides collaborative data training solutions by coordinating multiple hospitals to train and share encrypted federated models without leakage of data privacy.
Collective Intelligence: Decentralized Learning for Android Malware Detection in IoT with Blockchain
Specifically for malware detection task, (i) we propose a novel user (local) neural network (LNN) which trains on local distribution and (ii) then to assure the model authenticity and quality, we propose a novel smart contract which enable aggregation process over blokchain platform.
Trends in Vehicle Re-identification Past, Present, and Future: A Comprehensive Review
Vehicle Re-identification (re-id) over surveillance camera network with non-overlapping field of view is an exciting and challenging task in intelligent transportation systems (ITS).
A note on synthesizing geodesic based contact curves
The paper focuses on synthesizing optimal contact curves that can be used to ensure a rolling constraint between two bodies in relative motion.
Robotics
A Subword Guided Neural Word Segmentation Model for Sindhi
The word segmentation is a fundamental and inevitable prerequisite for many languages.
Treadmill Assisted Gait Spoofing (TAGS): An Emerging Threat to wearable Sensor-based Gait Authentication
We consider more realistic implementation and deployment scenarios than the previous study, which focused only on the accelerometer sensor and a fixed set of features.
Blockchain-Federated-Learning and Deep Learning Models for COVID-19 detection using CT Imaging
Blockchain technology authenticates the data and federated learning trains the model globally while preserving the privacy of the organization.
On the Inference of Soft Biometrics from Typing Patterns Collected in a Multi-device Environment
On the other hand, for regression tasks, we evaluated three ML and four DL-based regressors.
Touchless Typing using Head Movement-based Gestures
The modified GRU-based model outperforms the standard CNN-RNN and Conv3D models for three of the four scenarios.
Human-Computer Interaction I.2.7
Identification of Internal Faults in Indirect Symmetrical Phase Shift Transformers Using Ensemble Learning
This paper proposes methods to identify 40 different types of internal faults in an Indirect Symmetrical Phase Shift Transformer (ISPST).
Continuous Authentication Using One-class Classifiers and their Fusion
While developing continuous authentication systems (CAS), we generally assume that samples from both genuine and impostor classes are readily available.
Authenticating users through their arm movement patterns
The DFAR and DFRR increased from 5. 68% and 4. 23% to 15. 03% and 14. 62% respectively when feature level fusion-based design with classifier k-NN was tested under the inter-phase environment on a dataset of 12 users.
