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29 articles for “residual network”
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Optimized Residual Neural Network for Audio Spoof Detection in Speaker Verification Systems
Abstract: The Automatic speaker verification system is a type of biometric technology that utilizes speech to determine if a person is an authentic user or not. Unfortunately, such systems can be susceptible to audio-spoofing attacks. The proposed work deals with this problem of Audio Spoofing by employing Residual Networks to determine if a voice signal is bonafide or not. A comparative study of Mel-frequency Cepstral coefficients (MFCC), Constant Q Cepstral Coefficients …
Published in Current Trends in Signal Processing · Vol. 12, Issue 2, 2022 · pp. 19–32 Read article
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Optimizing Mango Harvest Timing in the Nasik Region (Maharashtra, India) by CNNs (Residual Network 101)
Abstract: The determination of optimal harvest timing is one of the most critical decisions in mango production, directly affecting postharvest quality, market value, transportation resilience, and export readiness. In regions such as Nashik, Maharashtra—one of India’s major fruit- producing belts—the climatic variability, cultivar differences, monsoon patterns, and market- driven pressures make accurate harvest timing essential. Traditional maturity assessment relies on subjective visual inspection, specific gravity, or destructive testing, each of which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 Read article
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Sentiment Analysis Using Emojis
Abstract: Sentiment analysis is a fast-growing research part in NLP (Natural Language Processing). It is fully focused on categorizing customer’s opinion about a particular product, blogs or comments etc. Public opinion has a significant impact on people's desire to contact with businesses, as well as overall brand perception. According to a Podium research, 93% of buyers believe online reviews affect their shopping decisions. Users may not give you another chance after …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 1, 2022 · pp. 43–46 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Comparative Analysis of MCNN and RCNN for Speech Emotion Recognition Using Gender Information
Abstract: Speech emotion recognition is a speech processing task and a computer-based approach designed to identify and classify the emotions conveyed in audio signals. The aim of this system is to evaluate a speaker's emotional state, such as happiness, anger, sadness, or frustration, by analyzing their speech patterns, which include prosodic features like pitch, frequency, and rhythm. Speech emotion recognition is used in various real-life scenarios that include Customer Service, Healthcare, …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 1, 2025 · pp. 1–10 Read article
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Revolutionizing Agriculture: Botani Scan’s Deep Learning for Plant Disease Diagnosis
Abstract: Crop disease detection is of key importance because of its role in food safety but infrastructural issues still hamper diagnosis in most regions worldwide. Accurate plant disease identification is essential to secure food, predicting yield decline and managing epidemic outbursts. The advent of digital cameras along with the progress of computer vision technology brings to light the mounting demands for the development of automated disease detection methods in precision agriculture, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 Read article
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An Energy efficient routing algorithm for heterogeneous Wireless Sensor Network
Abstract: Wireless sensing network is con- sisting of sensors and sink that is self- organized and infrastructureless network. En- ergy plays a very important role for the life- time, coverage and connectivity of network. In this paper, proposed protocol has two level heterogeneous wireless sensor network inwhich Residual Energy and distance of node from base station in which every sensing ele- ment node is taking into account to maximize the life …
Published in Recent Trends in Sensor Research & Technology · Vol. 8, Issue 1, 2021 Read article
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Artificial Intelligence and Constitutive Modeling Equations for Predictive Design of High-Performance Polymer Composites
Abstract: Growing polymer composite applications demand accurate mechanical prediction, yet complex interactions and conventional constitutive models limit predictive capability and require extensive calibration. To report these challenges, this research recommends a combined Artificial Intelligence (AI) and constitutive modeling approach based on an Enhanced Tasmanian Devil Optimizer-tuned Residual Neural Network with Multilayer Perceptron (ETDO-ResNet-MLP) for the predictive design of high-performance polymer composites. The study uses a publicly available Polymer Composite Property Dataset …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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An Energy efficient routing algorithm for heterogeneous Wireless Sensor Network
Abstract: Wireless sensing network is con- sisting of sensors and sink that is self- organized and infrastructure less network. En- ergy plays a very important role for the life- time, coverage and connectivity of network. In this paper, proposed protocol has two level heterogeneous wireless sensor network in which Residual Energy and distance of node from base station in which every sensing ele- ment node is taking into account to maximize …
Published in Recent Trends in Sensor Research & Technology Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Selection of Cluster Head in Wireless Sensor Network towards Extending Network Life Time
Abstract: Reduced energy consumption and extended lifetime are basic requirements of Wireless Sensor Network (WSN) with distributed nature and dynamic topological changes. The motes are arranged in clusters and only one mote is chosen as cluster head to synchronize and data routing. The proposed work introduces an innovative approach of choosing cluster head in artificially intelligent wireless sensor network. In the proposed work, the residual energy consumption plays the major role …
Published in Journal of Microcontroller Engineering and Applications · Vol. 3, Issue 3, 2016 · pp. 1–10 Read article
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Compare Three Reactive Routing Protocols in Grid based Cluster Wireless Sensor Network using Qualnet Simulator
Abstract: AbstractThis paper is comparing the performance of three different routing protocols in grid based clustering for wireless sensor network. Sensor network is keeping limited energy of sensor node send limited battery power. However the main task of sensor network energy consumption for sensor nodes. Furthermore grid based sensor working depend on location based that is divided into different parts. In grid based wireless sensor network, cluster head it works like …
Published in Journal of Communication Engineering & Systems · Vol. 4, Issue 1, 2014 · pp. 6–12 Read article
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Digital Twin Assisted Intelligent Prediction of Polymer Composite Degradation Under Environmental Exposure
Abstract: Polymer matrix composites (PMCs) deployed in aerospace, marine, automotive, and renewable-energy structures are continuously subjected to coupled environmental stressors — ultraviolet (UV) radiation, moisture ingress, thermal cycling, and mechanical loading — that progressively degrade their mechanical performance. Conventional accelerated ageing tests and empirical lifetime models are time-consuming, destructive, and poorly suited to in-service, asset-specific degradation forecasting. This paper proposes a Digital Twin (DT) assisted intelligent prediction framework that fuses a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Assessment of Matrix Cracking and Fiber Breakage in Hybrid Composite Materials.
Abstract: Hybrid composite materials, combining two or more distinct fiber or matrix constituents, have emerged as advanced structural solutions for aerospace, automotive, marine, and civil engineering applications. However, their complex microstructure makes them susceptible to multiple interacting damage mechanisms, particularly matrix cracking and fiber breakage. This study provides a comprehensive assessment of these damage modes, emphasizing their initiation, evolution, and combined effects on the mechanical integrity of hybrid composites. Matrix cracking …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Design and Implementation of an Energy-Efficient Wireless Sensor Network for Remote Monitoring
Abstract: Applications such as industrial automation, environmental monitoring, and agriculture make extensive use of wireless sensor networks, or WSNs. Since sensor nodes frequently operate in remote locations and have limited battery power, energy efficiency is the largest problem in WSN design. This paper presents an energy-efficient WSN architecture that combines optimized clustering and duty-cycling mechanisms to reduce energy consumption and increase network lifetime. The system uses low-power ESP32 nodes with Zigbee …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 22–27 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Molecular Docking, QSAR Modeling, and ADMET Evaluation of Novel Pyrazolo-Pyrimidine Derivatives as Potential CDK-2 Inhibitors for Cancer Therapy
Abstract: Cyclin-dependent kinase-2 (CDK-2) is an essential regulator in cell cycle progression and is an important therapeutic target in cancer drug development. In the present study, an integrated computational approach involving molecular docking studies, QSAR modeling, ADMET prediction, and artificial intelligence-based analysis was used to identify pyrazolo-pyrimidine derivatives as potential CDK-2 inhibitors. Based on the molecular docking results, it was found that selected compounds exhibited high binding affinity towards the ATP …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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Multifunctional Corn Husk Fibre/PLA–PBAT Hybrid Composites with Carbon-Black Percolation for Structural Self-Sensing Applications
Abstract: This study developed multifunctional polymer composites based on a PLA/PBAT (Polylactic Acid/ Poly(butylene adipate-co-terephthalate)) thermoplastic matrix reinforced with 20 wt.% corn husk fibre (CHF) and functionalized with conductive carbon black (CB) for smart consumer-electronics casings. Alkali treatment modified the lignocellulosic fibre surface, improving fibre–matrix interfacial adhesion and stress transfer within the polymer composite. Thermal characterization showed that the PLA cold-crystallization temperature decreased from 112.5 °C for the unfilled blend to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Determination of Free Chlorine Water Content in Jalandhar City Using Colorimeter
Abstract: Water is the ultimate source of life on this universe. Water is vital for the survival of humans, animals, and plants, and the issue of freshwater is becoming increasingly critical in society. With the human body composed of 64% water, contaminated water, inadequate waste disposal, and poor water management contribute to severe public health issues such as cholera, typhoid, and malaria annually. Globally, the quality and quantity of water are …
Published in Journal of Water Pollution & Purification Research · Vol. 11, Issue 1, 2024 · pp. 1–5 Read article
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Image Processing and Deep CNN-based Automatic Liver Cancer Detection
Abstract: Liver cancer ranks among the leading causes of mortality for people worldwide. In the current situation, manually identifying the cancer tissue is a challenging and timeconsuming task. Treatment planning, response monitoring, tumor load assessment, and prediction are all made possible by the segmentation of liver lesions in CT scans. To address the current problem of liver cancer, the Hybridized Fully Convolutional Neural Network (HFCNN), which has been theoretically modeled, has …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 39–41 Read article