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76 articles for “feature representation”
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Improving Reliability of Deep Learning System Under Distribution Shift Via Feature-Space Out-of-Distribution Detection
Abstract: Deep learning systems achieve strong predictive performance under independently and identically distributed conditions; however, their reliability can decline significantly when exposed to distribution shifts during deployment. This decline is often accompanied by overconfident predictions, which can introduce serious risks in safety-critical applications. In this work, we explore whether explicitly modeling the structure of the latent feature space can improve reliability through more effective out-ofdistribution detection. A statistically grounded framework based …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 66–76 Read article
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Cyber Security Implementation Through Deep Learning Based Fraudulent URL Detection
Abstract: A malicious URL, sometimes known as Spam, malicious ads, and drive-by vulnerabilities may all be found on a site that is malevolent. To find rogue URLs, you need to be quick. Researchers previously used blacklisting, regular expression searching and signature matching in their investigations. These strategies are worthless for discovering new malicious URLs or updated versions of previously problematic URLs. A machine learning-based approach may be developed to overcome this …
Published in Recent Trends in Programming languages · Vol. 9, Issue 2, 2022 · pp. 35–42 Read article
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Advances in Deep Learning for Medical Image Analysis in the Era of Precision Medicine
Abstract: Medical imaging is fundamental to modern healthcare but analyzing the high-dimensional data requires advanced techniques. Manual image interpretation is time-consuming, subjective and limited in detecting complex patterns and minute details. Recent breakthroughs in Deep Learning offer transformative advances for unlocking clinically relevant information from medical images. This paper provides a comprehensive 6000+ word review of the current state-of-the-art Deep Learning techniques for medical image analysis including detailed coverage of key …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 10–23 Read article
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Self-Supervised Learning for Early Disease Detection in Low-Label Medical Image Datasets
Abstract: Getting reliable labeled data for medical image analysis is genuinely difficult. Radiologists, pathologists, and other specialist clinicians are expensive, slow, and not universally available — particularly in low-resource clinical environments across developing nations. Unlike natural image benchmarks such as ImageNet, which provide millions of meticulously labeled training examples, most publicly accessible medical imaging repositories offer only a few hundred to a few thousand annotated scans. Supervised deep learning models trained …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 3, 2026 Read article
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Attention-Enhanced YOLO Framework for Robust Real-Time Object Detection in Autonomous Driving Environments
Abstract: Accurate object detection is essential for autonomous driving systems, where vehicles must continuously perceive surrounding road users and infrastructure in real time. Although the You Only Look Once (YOLO) family of deep learning detectors has achieved significant success due to its high speed and efficiency, detecting small or partially occluded objects in complex traffic environments remains challenging. This paper presents an attention-enhanced YOLO framework designed to improve feature representation and …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 2, 2026 · pp. 41–52 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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A Novel WPFM-Transformer Framework for DNA Sequence Classification using FASTA Data
Abstract: The identification of genetic variants, tracing of disease-associated mutations, and the reconstruction of evolutionary relationships from raw sequence data are all achieved by the analysis of DNA sequence. The FASTA format is plain text and is an easy-to-read format, which is why it has endured four decades of the field's growth into bioinformatics. Classical alignment programs like BLAST and Smith-Waterman work well with small data sets, but are limited by …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Aspect-Based Sentiment Analysis Using a Hybrid Approach with Dependency Parsing
Abstract: The rapid expansion of digital communication has resulted in an unprecedented volume of consumer-generated textual data across online reviews, social media platforms, forums, and e-commerce websites. Extracting meaningful insights from this data is increasingly important for organizations seeking to understand customer opinions, preferences, and behavioral trends. Despite significant advances in sentiment analysis, many existing approaches primarily focus on surface-level features and often overlook deeper syntactic and semantic relationships within text. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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Ocean Surface Features Extraction using Morphological Techniques from Sentinel-1A Data
Abstract: SAR (Synthetic Aperture Radar) imagery of the ocean surface obtained from remote sensinginstruments is one of the prominent research areas. In this paper, detection of oceanicfeatures from SAR using morphological technique is proposed. The detected surface featuresare presented in layered form. The main advantage of such representation is features can beeasily enabled or disabled on SAR image. Algorithm is tested on Sentinel-1A dataset of oceansurface.Keywords: SAR Images, Surface Features, Layered …
Published in Journal of Remote Sensing & GIS · Vol. 11, Issue 2, 2020 · pp. 1–4 Read article
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Improved Face Recognition Rate Based on PCA and LDA Using Image Preprocessing Techniques
Abstract: Principal component analysis (PCA) and linear discriminant analysis (LDA) are two powerful tools utilized for dimensionality reduction and feature extraction in most of pattern recognition applications. PCA selects features important for class representation while LDA algorithm selects features that are most effective for class separability. This paper carries out a comparative study of the two important algorithms in the context of enhancement obtained using certain image preprocessing techniques. The implementation …
Published in Journal of Instrumentation Technology & Innovations · Vol. 5, Issue 2, 2015 · pp. 19–24 Read article
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Monitoring of Unauthorized Identity and Access Behaviour for Outsourced Data in Cloud Environment
Abstract: The outsourcing of data is a significant challenge in the modern cloud computing ecosystem when it comes to tracking unauthorized identification and access behaviour. In order to overcome this issue, this research suggests a thorough method for reliable anomaly detection in cloud systems. Improving data security and offering a trustworthy monitoring system are the two main goals. The suggested approach proceeds methodically, gathering information from several sources such as user …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 9–19 Read article
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The Transient Performance of Power Line Towers
Abstract: This paper presents a refined approach to the transient analysis of power line towers. Each section of the tower’s steel structure is accurately modeled as a non-uniform transmission line. Among other features, an efficient representation of the towers’ cross-arms as open-ended non-uniform lines and their subsequent approximation by lumped capacitors will be explored. Furthermore, the error introduced by neglecting the presence of the cross-arms, as well as the effect of …
Published in Trends in Electrical Engineering · Vol. 3, Issue 2, 2013 · pp. 20–28 Read article
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Age Estimation Using Artificial Intelligence Techniques: A Closure Look
Abstract: Important characteristic of human life is age, with the help of different patterns this can be concluded rising from the facial appearance. Many of the real-time applications such as safety manipulate and surveillance tracking, biometrics, cosmetology, entertainment, forensic art, electronic customer relationship management make machine based age estimation, especially frequent subject. It is the responsibility of facial pictures category to estimate the age. Its definition includes the determination of person’s …
Published in Journal of Operating Systems Development & Trends · Vol. 3, Issue 2, 2016 · pp. 15–22 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Dimensionality Reduction using Eigenfaces and Fisherfaces for Face Recognition Applications using Kernel LMS Algorithm
Abstract: AbstractFace recognition is an intricate numerical technology in computer systems that can support recognition of human faces using methods such as principal component analysis (PCA), linear discriminant analysis (LDA), etc. by comparing the given facial uniqueness with the already available face database. PCA and LDA are classical feature extraction and data representation techniques used in face recognition algorithm involving unsupervised statistical methods. The 2-D facial image can be transformed into …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 29–55 Read article
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Standard for Exchange of Products (STEP) based feature Recognition System for Prismatic Parts
Abstract: Feature extraction is considered as the bridge between Computer Aided Design (CAD) and Computer Aided Process Planning (CAPP). This work is concerned with understanding the problem of how to manipulate and extract information from CAD solid models by using Standard for Exchange of Product data model (STEP) files and its further use in downstream manufacturing operations. Emphasis is placed on recognizing and classifying manufacturing features from the Boundary Representation (BREP) …
Published in Journal of Production Research & Management · Vol. 1, Issue 1-2-3, 2011 · pp. 73–91 Read article
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Controlled Temporal Feature Ablation and Explainable Ensemble Learning for Next- Hour Residential Electricity Forecasting
Abstract: Short-term residential load forecasting is increasingly used in demand response, home energy management, and data-driven grid operation, yet reported gains are often difficult to attribute to either the forecasting algorithm or the temporal representation supplied to it. This study presents a controlled, leakage-aware evaluation of temporal feature engineering for one-hour-ahead household electricity forecasting. The public UCI Individual Household Electric Power Consumption dataset was aggregated to hourly resolution, causally imputed using …
Published in Trends in Electrical Engineering · Vol. 13, Issue 3, 2023 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article