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73 articles for “Feature Extraction”
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Sound-based Bird Classification Using Perceptual Features and Machine Learning: A Gaussian Mixture Model
Abstract: Classification of birds based on their sound patterns and identification of bird species found in the chirping sounds of birds were experimented with using the feature extraction method. This work is beneficial in ornithology to study birds and their behavior based on their sounds. The proposed methods can automatically classify birds by different sound processing. The audio file of a bird’s sound recording is first cut into smaller samples, and …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 46–52 Read article
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Automated Image Captioning Using Xception–CNN and LSTM for Descriptive Sentence Generation
Abstract: Generating descriptive texts for images is a complex and challenging task that requires advanced deep learning techniques. This paper presents a descriptive sentence generator for images using a combination of convolutional neural networks and recurrent neural networks. The proposed model utilizes a pretrained convolutional neural network, Xception, to extract image features, which are then processed by a long short-term memory network to generate meaningful textual descriptions. The model is trained …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 20–28 Read article
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A Comprehensive Review of Convolutional Neural Network Architectures and Evolution
Abstract: Convolutional Neural Networks (CNNs) have become a foundational deep learning framework in computer vision because they can automatically extract layered, increasingly complex features directly from raw image data. CNNs use convolutional, pooling, and activation layers to extract spatial patterns from basic edges to intricate object components, drawing inspiration from the human visual cortex. An overview of CNNs’ basic architecture is given in this study, along with an explanation of important …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 32–40 Read article
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Deep Learning in Medical Image Classification and Object Detection: A Survey
Abstract: Deep learning methods have demonstrated superior performance in the area of computer vision, speech recognition, natural language processing, healthcare, and many more. Convolutional neural networks (CNNs) are a class of deep learning methods that have the ability to learn from raw data available as images, audio, or text. CNNs have become a powerful tool for variety of pattern recognition tasks due to the availability of abundant data and GPU-based training. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 1–15 Read article
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Genre Classification of Music Using Machine Learning
Abstract: One of the most important technological advances of the 21st century is artificial intelligence (AI) and machine learning. They are revolutionizing computers, banking, healthcare, agriculture, music and travel. A strong model has mastered many difficult learning tasks. Speech analysis is one area of artificial intelligence. This includes finding information about music, creating music, and categorizing music. Music data is one of the most complex source data available today. This is …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 17–28 Read article
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Redundant Keypoint Elimination Using Redundancy Index on Basic SIFT Algorithm
Abstract: ABSTRACT Matching features across different images is a common problem in computer vision. For the images of different scales and rotations, there is the need of scale-invariant feature transform (SIFT). SIFT identifies the distinctive keypoints that are invariant to location, scale, rotation, robust to affine transformations (changes in scale, rotation, shear, and position) and changes in illumination, which are usable for object recognition. SIFT algorithm includes two main stages: feature …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 1, 2019 · pp. 22–31 Read article
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Facial Expression Classification using Multi-Scale Histogram of Oriented Gradients
Abstract: An automatic facial expression classification method, based on multiscale Histogram of Oriented Gradients (HOG) features extracted from sub-facial image patches, is proposed in this paper. A number of multiclass Support Vector Machines (SVM) are designed using the multiscale HOG features for classifying six basic facial expressions for frontal face images. The proposed method, with a simple design and few training data, achieves descent classification accuracy at a very low computational …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 1, 2020 · pp. 5–13 Read article
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Predictive Models for Drinking Water Quality: Leveraging Machine Learning for Improved Safety and Efficiency
Abstract: Quality of drinking water is one of the critical determinants of public health, leading to severe environmental and health-related issues when poor. The paper examines the integration of machine learning techniques that could improve accuracy and efficiency in assessing drinking water quality. The traditional techniques of monitoring drinking water are resource-intensive yet lack timely insight into contamination events. In this scenario, an evaluation of the performance of ML models such …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 1, 2025 Read article
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Vehicle Number Plate Detection and Recognition System in Nigeria Using Deep Learning
Abstract: With over 200 million citizens, Nigeria is one of Africa’s largest and most populous nations. It is now essential to automate traffic management due to the rising number of vehicles in the nation. With the use of a deep learning technique known as the YOLO method, the study was able to construct an automatic vehicle license plate identification system that will recognize each of the vehicle license plates when many …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 32–45 Read article
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AI-Based Deepfake Voice Detection Model for Hindi Language
Abstract: Most current research on deepfake voice detection focuses heavily on English or Mandarin, creating a significant security gap for Hindi speakers. To address this, we developed a detection framework specifically tailored for the Hindi language using a lightweight approach: Mel-Frequency Cepstral Coefficient (MFCC) feature extraction paired with an XGBoost classifier. We trained the system on a large dataset comprising over 99,000 real voice samples and roughly 3,800 synthetic samples, each …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 2, 2026 Read article
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Detailed survey on detection of Dirtiness of PV panels using different approaches
Abstract: The accumulation of dust, dirt, bird droppings, pollen, and other environmental contaminants on photovoltaic (PV) panels significantly reduces their power generation efficiency and increases operational and maintenance costs. Therefore, timely and accurate detection of the cleanliness condition of solar panels is essential for maintaining optimal energy production, improving system reliability, and extending the operational lifespan of PV installations. In recent years, considerable research interest has been directed toward automated soiling …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Classification of power quality disturbances using advanced deep learning algorithms for Accurate and efficient electrical signal analysis
Abstract: Power systems today have to deal with more and more power quality issues (PQDs) like voltage drops, rises, harmonics, and transients because more people are using renewable energy sources and electronic devices. These problems can hurt equipment, stop services, and lower the overall reliability of power. In real-time settings, traditional detection methods often don't work as quickly or accurately as they should. This paper looks at how deep learning models, …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 2, 2026 Read article
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AI-Based Image Detection of Rice Crop Diseases Using Deep Learning and Grad-CAM
Abstract: The Indian economy relies heavily on agriculture, and rice is one of the most significant staple crops grown in the country. Nevertheless, rice cultivation faces numerous challenges due to several leaf diseases, such as bacterial leaf blight, brown spot, and leaf smut. These diseases can lead to substantial yield losses and financial burdens for farmers. Therefore, the early detection and classification of these diseases are essential to minimize crop damage …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 Read article
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Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model
Abstract: Diabetic retinopathy (DR) is a leading cause of blindness worldwide, impacting the largest number of individuals who have diabetes. Early identification of diabetic retinopathy may help to prevent severe effects; however, the very limited availability of labeled datasets, and the possibility of overfitting of the model, presents obstacles to obtaining an accurate diagnosis. In this research, a hybrid deep learning strategy is introduced, where Generative Adversarial Networks (GANs) are used …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article
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AI-Driven Hybrid Neural Network Architecture for Medical Image Segmentation: A Novel Approach for Early Disease Detection
Abstract: One of the key factors in detecting early diseases is medical image segmentation. Medical image segmentation can be very complex due to the differences in image quality, noise, and specific anatomical structures of individual patients. A novel approach for a hybrid neural network structure that combines the power of convolutional neural networks, and the transformer-based models is described here for improved accuracy and robustness of medical image segmentation. Unlike traditional …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 1–7 Read article
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Improved Approaches of Image Forgery Detection using SURF and 4-level DWT
Abstract: ABSTRACT Today, there are various types of image tampering techniques, and copy-move forgery is one of them in which a piece of the picture is copied and pasted on another part of a picture. The study reviewed the several methods proposed to achieve this goal. This method generally uses both the feature point-based and the block-based algorithm. We use DWT (discrete wavelet transforms) for the decomposition of an image into …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 2, 2018 · pp. 1–8 Read article
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Face Recognition and Identification Using Computer Vision
Abstract: ABSTRACT In practice, identification of criminal in India is done through thumbprint identification. However, this type of identification has many constraints. Our face recognition poses to be able to detect face and recognize face automatically. Nowadays, face recognition systems use biometric for many security applications. This technique uses an image-based approach toward artificial intelligence by removing redundant data from face images through image compression using computer vision that compares a …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 1, 2019 · pp. 6–10 Read article
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Detection of Leaf Diseases Using Image Processing Techniques
Abstract: Agricultural field plays a vital role in the earning to feed ever growing population. The productivity of the crop depends on pest attack, disease, weather, etc. The disease in plants will affect the production of crops. Detecting diseases in plants through visualization is a traditional method which is not relevant. We are focusing on reliable, fast and accurate detection method that can be done using image processing techniques to monitor …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 2, 2019 · pp. 14–19 Read article
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ANN Based Power Quality Identification and Classification in Wind Solar Hybrid System
Abstract: With the development of new functionalities solar and wind energy based hybrid system are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting is one of the most promising sources. Due to the development of modern power electronics devices the power quality of wind solar hybrid system gets affected. Hence due to the increasing usage of sensitive electronic equipments in wind solar …
Published in International Journal of Electrical Power System and Technology · Vol. 3, Issue 2, 2017 · pp. 6–11 Read article
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Analysis of EEG Signal for Brain Computer Interface
Abstract: Brain-computer interface (BCI) frameworks causes a subject to issue commands to an electronic device just by methods for brain activity. EEG has wide applications in the brain-computer interface (BCI) systems. Sadly, the spatial resolution of EEG is very low, because of the volume conduction. While measuring signals related to motor movements various artefacts also get added. We have studied pre-processing techniques and classification techniques which improve performance. While there are …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 2, 2020 · pp. 6–11 Read article