498 hasil
Menampilkan 1–20 · 0,13 detik · RSS
ICTACT Journal on Image and Video Processing
ISSN 0976-9099 · ICT Academy of Tamil Nadu · 498 artikel di indeks
-
Artikel Jurnal Teks lengkap
DEVELOPMENT OF FIRASS: A NOISE-RESILIENT FACIAL IMAGE ENHANCEMENT SYSTEM FOR CUSTOMER EMOTION RECOGNITION
The accuracy of facial emotion recognition systems largely depends on the quality of input images, particularly in interactive customer services where real-time data capture is generally noisy, low in lighting, and resolution-constrained. This paper proposes FIRASS (Facial Image Refinement and…
-
Artikel Jurnal Teks lengkap
A HYBRID CAD APPROACH USING VGG-16, RAS-UNET, AND CNN-MGCA FOR MICROANEURYSM DETECTION IN DIABETIC RETINOPATHY
Detecting red lesions in color retinal fundus images is essential for preventing vision loss and blindness in people with diabetic retinopathy (DR). Among these lesions, microaneurysms (MAs) are the earliest and most common indicators of DR, making their identification particularly important for…
-
Artikel Jurnal Teks lengkap
PREDICTION OF ABNORMAL NEURAL CIRCUITS FOR DIAGNOSIS OF ALZHEIMER’S DISEASE
Alzheimer’s disease (AD) is a neurological condition that causes memory loss and cognitive impairment and is gradual and irreversible. Timely intervention and a better quality of life for a patient are possible only through early and accurate diagnosis. This paper seeks to model abnormal neural…
-
Artikel Jurnal Teks lengkap
DA-MMHAR: DOMAIN-ADAPTIVE MULTIMODAL AI MODELS FOR CROSS-USER AND CROSS-ENVIRONMENT HUMAN ACTIVITY RECOGNITION
Human Activity Recognition (HAR) systems have demonstrated excellent performance in controlled laboratory settings, but their performance tends to vary significantly when applied to diverse users, devices, and environments across domains. To overcome the above-mentioned limitation, this paper…
-
Artikel Jurnal Teks lengkap
SUPERVISED DEEP LEARNING ON HYBRID APPROACH OF COMPRESSED CONTOUR-INFORMED TEXTURE FEATURE APPROACH FOR PALMPRINT RECOGNITION
Biometric technology protects valuable assets and digital data by utilizing human physical and behavioral traits. Among these traits, palmprint recognition is recognized as particularly effective due to its unique characteristics. This paper introduces a new method called the Hybrid Approach of…
-
Artikel Jurnal Teks lengkap
CSDE: A CORRELATION-BASED EVOLUTIONARY APPROACH FOR 3D FACE DEPTH ESTIMATION
Estimation of Depth (z-coordinate) of 3D face from 2D (x-, y-) face images based on similarity transform is an optimization problem. In this work Correlation Scale Factor Differential Evolution (csDE) is proposed and used to estimate the optimal depth values which represent the z-coordinate. The…
-
Artikel Jurnal Teks lengkap
ENHANCED BIAS MITIGATION AND SCRUPULOUS 3D RECONSTRUCTION IN 2D BRAIN MR IMAGING: A MULTI-LAYERED APPROACH
Computer Assisted Diagnosing (CAD) plays a vital role in healthcare education, surgical training and treatment planning. The backbone of CAD is medical images. The 2D medical images will lack the ability to interpret the information. 3D model construction helps to abolish the hurdle. The 2D medical…
-
Artikel Jurnal Teks lengkap
ADAPTIVE MULTIMEDIA OPTIMIZATION USING GENERATIVE ADVERSARIAL NETWORKS AND ATTENTION-BASED DEEP FEATURE LEARNING FRAMEWORK
Multimedia systems have faced persistent challenges in maintaining perceptual quality under dynamic network and computational constraints. Traditional optimization techniques have struggled to preserve visual fidelity while adapting to heterogeneous content distributions. A hybrid deep learning…
-
Artikel Jurnal Teks lengkap
HYBRID DEEP NEURAL VIDEO WATERMARKING FRAMEWORK WITH ATTENTION-DRIVEN ROBUST EMBEDDING AND INTELLIGENT TAMPER DETECTION
The rapid growth of digital multimedia sharing platforms increases the demand for secure video copyright protection and unauthorized content tracking. Conventional video watermarking approaches often suffer from low robustness, limited embedding capacity, and poor resistance against geometric and…
-
Artikel Jurnal Teks lengkap
SPATIOTEMPORAL FEATURE EXTRACTION AND REINFORCEMENT LEARNING FOR ADAPTIVE OPTIMIZATION OF MULTIMEDIA QUALITY IN DYNAMIC NETWORKS
Multimedia transmission systems have faced significant performance degradation due to dynamic network conditions and heterogeneous user demands. The background of adaptive multimedia optimization has remained critical in supporting real time quality of service requirements across modern…
-
Artikel Jurnal Teks lengkap
EVOLUTIONARY OPTIMIZED FUZZY CNN-BILSTM FUSION MODEL FOR VISUAL SENTIMENT FORECASTING IN SOCIAL MEDIA STREAMS APPLICATIONS
Social media platforms have generated massive visual content streams, where sentiment interpretation remains crucial for adaptive marketing and decision making. Problem: existing models have struggled to integrate spatial visual cues with temporal dependencies, which has limited forecasting…
-
Artikel Jurnal Teks lengkap
NEURO-FUZZY EVOLUTIONARY FRAMEWORK FOR CROSS-MODAL FORECASTING IN DIGITAL MEDIA SUPPLY CHAIN MANAGEMENT
Digital media supply chain systems have experienced rapid expansion due to increasing demand for real-time content distribution and adaptive forecasting mechanisms. However, the variability in cross-modal data streams has created significant uncertainty in predicting demand, resource allocation…
-
Artikel Jurnal Teks lengkap
ENHANCING DEGRADED HANDWRITTEN DOCUMENT RECOGNITION USING RESNET BASED CRNN MODEL WITH OPTIMIZED IMAGE ENHANCEMENT
Handwritten text recognition in degraded documents remains a major challenge in document image analysis due to factors such as noise, handwriting variability, uneven lighting, faded ink, and physical distortions in historical or low-quality scans. Traditional OCR methods often perform poorly under…
-
Artikel Jurnal Teks lengkap
METHOD OF MODIFIED POSE-INVARIANT FACE FRONTALIZATION USING CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS WITH L1–L2 LOSS REGULARIZATION
Pose variation in facial imagery presents a persistent challenge for automated face recognition systems, particularly in uncontrolled environments such as surveillance, access control, and mobile device authentication. This paper introduces an approach based on Conditional Generative Adversarial…
-
Artikel Jurnal Teks lengkap
ONION IMAGE CLASSIFICATION USING CNN MODELS
The quality of onions (Allium cepa), a vegetable that is consumed worldwide, is essential for food safety and agricultural economics. This study suggests a deep learning-based approach that uses convolutional neural networks (CNNs) to categorize images of onions as either healthy or unhealthy. The…
-
Artikel Jurnal Teks lengkap
EFFICIENT PAVEMENT CRACK DETECTION FOR REAL-TIME ROAD MAINTENANCE USING DEEP LEARNING MODELS
Pavement crack detection needs to be done to identify and assess cracks in road surfaces. Detecting the crack and its measurement by manual methods is extremely time-consuming and requires a lot of manpower. This process is crucial for maintaining road safety and infrastructure integrity. By…
-
Artikel Jurnal Teks lengkap
ACTIVE DEEP ENSEMBLE LEARNING FRAMEWORK FOR AUTOMATED SURGICAL VIDEO SEGMENTATION AND EFFICIENT ANNOTATION IN MINIMALLY INVASIVE PROCEDURES
Surgical video analysis has become an essential component in computer-assisted interventions and clinical documentation. The rapid growth of minimally invasive surgery has produced large volumes of surgical recordings that require detailed frame-level annotations for training intelligent systems…
-
Artikel Jurnal Teks lengkap
HYBRID METAHEURISTIC OPTIMIZATION FRAMEWORK FOR COMPRESSIVE BACKPROPAGATION BASED NEURAL IMAGE REPRESENTATION LEARNING AND RECONSTRUCTION
The rapid growth of visual data has increased the demand for efficient image representation techniques that reduce storage and computational requirements while preserving structural information. Neural networks have provided powerful mechanisms for learning compact image representations, yet…
-
Artikel Jurnal Teks lengkap
A MULTIMODAL FUSION TRANSFORMER FRAMEWORK FOR ROBUST AUDIO-VISUAL TEXTUAL SENTIMENT ANALYSIS IN SOCIAL MEDIA CONTENT
Sentiment analysis in social media has gained substantial attention due to the rapid growth of multimedia content across digital platforms. Traditional sentiment analysis techniques primarily relied on textual information, which has limited the capability of capturing the rich emotional cues that…
-
Artikel Jurnal Teks lengkap
CONTENT-AWARE NEURAL VIDEO COMPRESSION WITH SPATIALLY ADAPTIVE RATE–DISTORTION OPTIMIZATION FOR EFFICIENT HIGH-QUALITY VIDEO TRANSMISSION
The rapid growth of multimedia communication has significantly increased the demand for efficient video compression techniques. Conventional video coding standards often rely on fixed or globally optimized rate–distortion strategies that inadequately adapt to spatial content variations across video…