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82 articles for “local features”
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Research ArticleOpen accessIn the abstractAn Edge Efficient and Lightweight Hybrid CNN Vision Transformer Network With CBAM for IoT Based Plant Disease DetectionNyabeye Pangop Doris-Khöler, Kengni Ngangmo OlgaDetecting crop disease early enough to act on it remains a bottleneck for smallholder and precision farming alike, particularly when diagnosis depends on manual inspection or lab analysis that cannot keep pace with an outbreak. We present AgriViTNet, a compact CNN-Vision Transformer hybrid built for exactly this constraint: It extracts local texture cues through convolution, relates them across the whole … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 578 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Sentiment Analysis for Malayalam With mBERT: A Profoundly Transparent and Accurate Approach Using LIMEAnitha R., K. S. Anil Kumar, Rajeev R. R. et al.The overlapping sentiment boundaries, intensifiers, and intricate morphological structures in Malayalam present particular difficulties for sentiment analysis, making it hard for traditional machine learning techniques to produce consistent results. We present an explainable sentiment analysis framework in this paper that refines a Multilingual Bidirectional Encoder Representations from Transformers (mBERT) model on a novel constituency-level dataset that has been manually curated … …Journal of Computer Science, Vol. 22, Issue 5 · 2 Jun 2026 · 1,061 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,481 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Deep Learning Model for Evaluating Subjective Answers Based on Semantic Textual SimilaritySiddhesh Kudtarkar, Kavita ShirsatSubjective answer evaluation requires accurately identifying semantic similarities between student and reference responses. This study introduces a Hybrid Deep Learning Model (HDLM) that integrates CNN, GRU, and LSTM architectures to assess Semantic Textual Similarity (STS) more effectively. The HDLM employs two parallel branches-CNN-GRU and CNN-LSTM to capture both local syntactic features and long-range contextual dependencies, followed by Manhattan distance for … …Journal of Computer Science, Vol. 22, Issue 4 · 7 Apr 2026 · 1,690 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Self-Esteem and Body Dissatisfaction Among Jamaican Youths: Unraveling Influential Factors and Promoting Positive Self-ImageDenise LloydThis qualitative study explores body image and self-esteem perceptions among Jamaican youths aged 9-15, framed within a Participatory Action Research (PAR) approach. PAR, grounded in critical theory and social constructivism, emphasizes collaborative inquiry, cyclical reflection, and action to address social issues relevant to the participants' lived experiences. This methodology is particularly suited for youth-centred, culturally situated research, as it empowers … …Current Research in Psychology, Vol. 11, Issue 1 · 9 Jan 2026 · 3,367 accessesView PDFCite
Research ArticleOpen accessIn the abstractLocal Binary Pattern for the Evaluation of Surface Quality of Dissimilar Friction Stir Welded Ultrafine Grained 1050 and 6061-T6 Aluminium AlloysAkshansh Mishra, Rajat SarawagiFriction Stir Welding process is an advanced solid-state joining process which finds application in various industries like automobiles, manufacturing, aerospace and railway firms. Input parameters like tool rotational speed, welding speed, axial force and tilt angle govern the quality of Friction Stir Welded joint. Improper selection of these parameters further leads to fabrication of the joint of bad quality resulting … …Journal of Mechatronics and Robotics, Vol. 4, Issue 1 · 27 Jul 2020 · 6,228 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Fleet Management with GPS Data in Port Terminals: A Deep Learning Architecture for Truck Position PredictionMohammed El Karkraoui, Hicham AttariuasEffective truck fleet management in port terminals is crucial for improving operational efficiency and reducing delays. However, GPS-based positioning systems often face limitations in port environments due to signal obstructions and network issues. This study explores the utilization of advanced methods for deep learning, particularly Recurrent Neural Networks (RNNs) for predicting truck positions when GPS signals are unavailable or unreliable. … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,395 accessesView PDFCite
Review ArticleOpen accessIn the abstractUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,107 accessesView PDFCite
Research ArticleOpen accessIn the abstractFusion of Features and Extreme Learning Machine for Facial Expression RecognitionBayezid Islam, Arfat HossainHuman emotion is highly correlated to facial expressions. Due to its growing demand in different sectors, an emotion recognition method is proposed through recognizing facial expressions. The input image is preprocessed and then the resulting image is segmented into four facial expression regions following the newly proposed segmentation method. Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are … …Journal of Computer Science, Vol. 15, Issue 12 · 28 Dec 2019 · 7,404 accessesView PDFCite