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1978 articles for “CLA” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 Read article
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Machine Learning Approaches Towards Resume Classification
Abstract: Finding the right person for an open position can be an unnerving task, especially when there are many applicants, and if the recruiter or the Human Resources department must sort and further categorize all those resumes then it will be a labor-intensive, time-consuming, and tiresome task. Additionally, human assessment of resumes may be biased and prone to mistakes. Manually screening the proper candidate's resume from the pool is not practicable; …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article
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A Review on Ethnomedicinal Claims of Gloriosa Superba Linn. (Langali).
Abstract: Aim: Gloriosa superba Linn., is a procumbent herbaceous climber and different parts of G. superba, have wide diversity of uses especially in traditional system of medicine among local healers. The goal of the current review is to gather information on research updates and claims pertaining to ethno medicine and folklore that is currently accessible. Material and Methods: Information and data regarding reported ethno medicinal uses and folklore claims of the …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 11, Issue 2, 2024 · pp. 14–23 Read article
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Potential of Particle Size Mix Ratios of Plantain Ogoni Red with Clay Soil: The Integrity of Adsorbent Performance in AGO Treatment in Fresh Water Environment
Abstract: The research is focus on monitoring the performance of various formulated adsorbent mix ratio of clay soil with some agro-based materials in treatment of contaminated water environment. The agro-based material used was Plantain Ogoni Red (POR) and fresh water environment was used for this research. The agro-based material was processed into different particle sizes of 150 𝜇m, 300 𝜇m, 600 𝜇m and 1.18 mm and the clay soil into fine …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 3, 2024 · pp. 12–25 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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Effect of Bacteria on Crude Oil Degradation in Loamy and Clay Soil for Water and Ethanol Biostimulant Extraction from Bryophylum pinnatum Leaf
Abstract: The effect of bacteria on crude oil degradation in loamy and clay soil for water and ethanol biostimulant extraction from Bryophylum pinnatum leaf was investigated to ascertain the potential of the bacteria counts in the bioreactors sampled. At the progressive phase, the bacteria counts were more with bioreactors induced with ethanol solvent extract as the volume of the dosage increases compared to the bioreactors induced with the water extract. The …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–25 Read article
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The Impact of Spiritual Well Being on Self Concept Clarity and Emotional Intelligence Among Adults
Abstract: Spiritual well-being (SWB) plays a vital role in shaping psychological resilience, emotional regulation, and self- awareness. This study examines the impact of spiritual well-being (SWB) on self-concept clarity (SCC) and emotional intelligence (EI) in adults aged 20-40, while also exploring age and gender differences. SWB, defined as a sense of purpose, inner harmony, and connectedness, influences psychological resilience and emotional regulation. Using the Spiritual Well-Being Scale (SWBS), Self-Concept Clarity Scale …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 50–58 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
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Microbial Population Dynamics during Phytobioremediation of Hydrocarbon- Contaminated Swampy and Clay Soils
Abstract: Soil contamination by petroleum hydrocarbons remains a critical environmental challenge, particularly in wetland and clay-rich ecosystems where natural attenuation processes are often limited. This study investigates the response of total heterotrophic bacteria (THB) during the bioremediation of hydrocarbon-contaminated swampy and clay soils amended with Moringa oleifera biomass and elephant grass (Pennisetum purpureum). The objective was to evaluate microbial population dynamics under varying amendment dosages and to identify treatment conditions favorable …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 1, 2026 · pp. 31–35 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 10–22 Read article
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Barg-e-Tulsi (Ocimum sanctum Linn.) in Unani Medicine: Bridging Classical Therapeutics with Contemporary Pharmacological Evidence
Abstract: In the Unani System of Medicine (USM), Barg-e-Tulsi (Ocimum sanctum Linn.), commonly known as Tulsi or Holy Basil, is a highly valued medicinal herb that has been extensively used for centuries in the prevention and treatment of various ailments. It occupies an important place in traditional Unani therapeutics due to its broad spectrum of medicinal properties and its effectiveness in managing respiratory, gastrointestinal, neurological, and infectious disorders. Classical Unani scholars …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 2, 2026 · pp. 20–29 Read article
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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Classification of Homogeneous and Heterogeneous Fog for Vision Enhancement
Abstract: Classification is the prior methodology to design vision enhancement algorithms to make them more efficient. In this reported work, mean intensity value and range of intensity level are proposed for the classification of camera images into homogeneous and heterogeneous fog due to turbid weather conditions for the first time. The use of average intensity and distribution of intensity of synthetic foggy images with different kind of fog are taken as …
Published in Current Trends in Signal Processing · Vol. 4, Issue 2, 2014 · pp. 7–10 Read article
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CBR Behaviour of Soil Treated with Class ‘F’ Fly Ash
Abstract: Disposal of fly ash available at thermal power stations is not only a serious national issue but also causes endanger to the mankind if not properly utilized and handled. The study aims at making effective utilization of Class ‘F’ fly ash by mixing with soil in suitable proportions and showcasing its usage to be adopted in subgrade as well as subbase components in pavement infrastructures. Silty sand was mixed with …
Published in Journal of Geotechnical Engineering · Vol. 3, Issue 1, 2016 · pp. 33–43 Read article