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A New Approach for Classification of Spices to make Special Herbal Tea using Caralluma Fimbriata (2024)
Journal Article
Kumar, P. P., Palaiahnakote, S., & Patil, R. (in press). A New Approach for Classification of Spices to make Special Herbal Tea using Caralluma Fimbriata. International Journal of Pattern Recognition and Artificial Intelligence,

Classification of multiple types of spice images is automatically challenging due to conflict between the texture patterns of spice images. This work aims to develop an automatic system for classifying different types of spice images so that the syst... Read More about A New Approach for Classification of Spices to make Special Herbal Tea using Caralluma Fimbriata.

A Robust Script Independent Handwriting System for Gender Identification (2024)
Journal Article
Palaiahnakote, S., Kaljahi, M. A., Kanchan, S., Pal, U., Lopresti, D., & Lu, T. (in press). A Robust Script Independent Handwriting System for Gender Identification. Expert systems with applications,

Gender identification at the word level in a multi-script environment is challenging due to variations posed by free-style handwriting of individuals and geographical differences in writing styles. This paper presents a new approach, Multi-Orientatio... Read More about A Robust Script Independent Handwriting System for Gender Identification.

Domain Independent Adaptive Histogram Based Features for Pomegranate Fruit and Leaf Diseases Classification Double blind (2024)
Journal Article
Palaiahnakote, S. (in press). Domain Independent Adaptive Histogram Based Features for Pomegranate Fruit and Leaf Diseases Classification Double blind. #Journal not on list,

Disease identification for fruits and leaves in the field of agriculture is important for estimating production, crop yield and earnings for farmers. In the specific case of pomegranates, this is challenging because of the wide range of possible dise... Read More about Domain Independent Adaptive Histogram Based Features for Pomegranate Fruit and Leaf Diseases Classification Double blind.

HLB Disease Detection in Omani Lime Trees Using Hyperspectral Imaging Based Techniques (2024)
Journal Article
Menezes, J., Dharmalingam, R., & Shivakumara, P. (2024). HLB Disease Detection in Omani Lime Trees Using Hyperspectral Imaging Based Techniques. https://doi.org/10.1007/978-3-031-53085-2_7

In the recent years omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus with no remedies or countermeasures to stop the disease... Read More about HLB Disease Detection in Omani Lime Trees Using Hyperspectral Imaging Based Techniques.

Altered Handwritten Text Detection in Document Images Using Deep Learning (2024)
Journal Article
Shivakumara, P., Patil, G., Gornale, S. S., & Lopresti, D. P. (in press). Altered Handwritten Text Detection in Document Images Using Deep Learning. #Journal not on list,

Handwritten documents possess immense significance in domains such as law, history, and administration. However, they are vulnerable to forgery, which can undermine their credibility and reliability. This paper aims to establish a dependable techniqu... Read More about Altered Handwritten Text Detection in Document Images Using Deep Learning.

A novel autoencoder for structural anomalies detection in river tunnel operation (2023)
Journal Article
TAN, X., Palaiahnakote, S., Chen, W., Cheng, K., & Du, B. (2024). A novel autoencoder for structural anomalies detection in river tunnel operation. Expert systems with applications, 244, https://doi.org/10.1016/j.eswa.2023.122906

Anomaly diagnosis is essential to prevent disasters and ensure long-term stable operation of tunnels. However, the diversity and scarcity of abnormal data make it difficult to identify outliers, especially to diagnose structural anomalies from poor-q... Read More about A novel autoencoder for structural anomalies detection in river tunnel operation.

A New Few-Shot Learning-Based Model for Prohibited Objects Detection in Cluttered Baggage X-Ray Images Through Edge Detection and Reverse Validation (2023)
Journal Article
Liu, K., Lyu, S., Shivakumara, P., Blumenstein, M., & Lu, Y. (2023). A New Few-Shot Learning-Based Model for Prohibited Objects Detection in Cluttered Baggage X-Ray Images Through Edge Detection and Reverse Validation. IEEE Signal Processing Letters, 30, https://doi.org/10.1109/LSP.2023.3326088

Detecting prohibited items via X-ray screening at airports and sensitive venues is essential for preventing smuggling and breaches of security. The difficulty in prohibited items inspection lies in accurately detecting prohibited items in complex X-r... Read More about A New Few-Shot Learning-Based Model for Prohibited Objects Detection in Cluttered Baggage X-Ray Images Through Edge Detection and Reverse Validation.

A New Language-Independent Deep CNN for Scene Text Detection and Style Transfer in Social Media Images (2023)
Journal Article
Shivakumara, P., Banerjee, A., Pal, U., Nandanwar, L., Lu, T., & Liu, C. (2023). A New Language-Independent Deep CNN for Scene Text Detection and Style Transfer in Social Media Images. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 32, 3552 - 3566. https://doi.org/10.1109/TIP.2023.3287038

Due to the adverse effect of quality caused by different social media and arbitrary languages in natural scenes, detecting text from social media images and transferring its style is challenging. This paper presents a novel end-to-end model for text... Read More about A New Language-Independent Deep CNN for Scene Text Detection and Style Transfer in Social Media Images.

Classification of aesthetic natural scene images using statistical and semantic features (2023)
Journal Article
Biswas, K., Shivakumara, P., Pal, U., Lu, T., Blumenstein, M., & Lladós, J. (2023). Classification of aesthetic natural scene images using statistical and semantic features. Multimedia Tools and Applications, 82, 13507–13532. https://doi.org/10.1007/s11042-022-13924-7

Aesthetic image analysis is essential for improving the performance of multimedia image retrieval systems, especially from a repository of social media and multimedia content stored on mobile devices. This paper presents a novel method for classifyin... Read More about Classification of aesthetic natural scene images using statistical and semantic features.

A Conformable Moments-Based Deep Learning System for Forged Handwriting Detection (2022)
Journal Article
Nandanwar, L., Shivakumara, P., A. Jalab, H., W. Ibrahim, R., Raghavendra, R., Pal, U., …Blumenstein, M. (2022). A Conformable Moments-Based Deep Learning System for Forged Handwriting Detection. IEEE transactions on neural networks and learning systems, 1-14. https://doi.org/10.1109/TNNLS.2022.3204390

Detecting forged handwriting is important in a wide variety of machine learning applications, and it is challenging when the input images are degraded with noise and blur. This article presents a new model based on conformable moments (CMs) and deep... Read More about A Conformable Moments-Based Deep Learning System for Forged Handwriting Detection.

An Episodic Learning Network for Text Detection on Human Bodies in Sports Images (2022)
Journal Article
Nath Chowdhury, P., Shivakumara, P., Raghavendra, R., Nag, S., Pal, U., Lu, T., & Lopresti, D. (2022). An Episodic Learning Network for Text Detection on Human Bodies in Sports Images. IEEE Transactions on Circuits and Systems for Video Technology, 32, 2279 - 2289. https://doi.org/10.1109/TCSVT.2021.3092713

Due to the proliferation of sports-related multimedia content on the WWW, effective visual search and retrieval present interesting research challenges. These are caused by poor image quality, a wide range of possible camera points of view, pose vari... Read More about An Episodic Learning Network for Text Detection on Human Bodies in Sports Images.

Mining text from natural scene and video images: A survey (2021)
Journal Article
Shivakumara, P., Alaei, A., & Pal, U. (2021). Mining text from natural scene and video images: A survey. Data Mining and Knowledge Discovery, 11(6), https://doi.org/10.1002/widm.1428

In computer terminology, mining is considered as extracting meaningful information or knowledge from a large amount of data/information using computers. The meaningful information can be extracted from normal text, and images obtained from different... Read More about Mining text from natural scene and video images: A survey.

A deep action-oriented video image classification system for text detection and recognition (2021)
Journal Article
Chaudhuri, A., Shivakumara, P., Nath Chowdhury, P., Pal, U., Lu, T., Lopresti, D., & Hemantha Kumar, G. (2021). A deep action-oriented video image classification system for text detection and recognition. SN Applied Sciences, 3, Article 838. https://doi.org/10.1007/s42452-021-04821-z

For the video images with complex actions, achieving accurate text detection and recognition results is very challenging. This paper presents a hybrid model for classification of action-oriented video images which reduces the complexity of the proble... Read More about A deep action-oriented video image classification system for text detection and recognition.

Anomaly Detection in Natural Scene Images Based on Enhanced Fine-Grained Saliency and Fuzzy Logic (2021)
Journal Article
Mokayed, H., Shivakumara, P., Saini, R., Liwicki, M., Chee Hin, L., & Pal, U. (2021). Anomaly Detection in Natural Scene Images Based on Enhanced Fine-Grained Saliency and Fuzzy Logic. IEEE Access, 9, https://doi.org/10.1109/ACCESS.2021.3103279

This paper proposes a simple yet effective method for anomaly detection in natural scene images improving natural scene text detection and recognition. In the last decade, there has been significant progress towards text detection and recognition in... Read More about Anomaly Detection in Natural Scene Images Based on Enhanced Fine-Grained Saliency and Fuzzy Logic.

A new context-based feature for classification of emotions in photographs (2021)
Journal Article
Krishnani, D., Shivakumara, P., Lu, T., Pal, U., Lopresti, D., & Hemantha Kumar, G. (2021). A new context-based feature for classification of emotions in photographs. Multimedia Tools and Applications, 80, 15589–15618. https://doi.org/10.1007/s11042-020-10404-8

A high volume of images is shared on the public Internet each day. Many of these are photographs of people with facial expressions and actions displaying various emotions. In this work, we examine the problem of classifying broad categories of emotio... Read More about A new context-based feature for classification of emotions in photographs.

DCT-phase statistics for forged IMEI numbers and air ticket detection (2021)
Journal Article
Nandanwar, L., Shivakumara, P., Kanchan, S., Basavaraja, V., Guru, D., Pal, U., …Blumenstein, M. (2021). DCT-phase statistics for forged IMEI numbers and air ticket detection. Expert systems with applications, 164, https://doi.org/10.1016/j.eswa.2020.114014

New tools have been developing with the intention of having more flexibility and greater user-friendliness for editing the images and documents in digital technologies, but, unfortunately, they are also being used for manipulating and tampering infor... Read More about DCT-phase statistics for forged IMEI numbers and air ticket detection.

A new unified method for detecting text from marathon runners and sports players in video (PR-D-19-01078R2) (2020)
Journal Article
Nag, S., Shivakumara, P., Pal, U., Lu, T., & Blumenstein, M. (2020). A new unified method for detecting text from marathon runners and sports players in video (PR-D-19-01078R2). Pattern recognition, 107, https://doi.org/10.1016/j.patcog.2020.107476

Detecting text located on the torsos of marathon runners and sports players in video is a challenging issue due to poor quality and adverse effects caused by flexible/colorful clothing, and different structures of human bodies or actions. This paper... Read More about A new unified method for detecting text from marathon runners and sports players in video (PR-D-19-01078R2).

Saliency-based bit plane detection for network applications (2020)
Journal Article
Asadzadeh Kaljahi, M., Shivakumara, P., Hakak, S., Yamani Idna Idris, M., Hossein Anisi, M., & Rajan, D. (2020). Saliency-based bit plane detection for network applications. Multimedia Tools and Applications, 79, 18495–18513. https://doi.org/10.1007/s11042-020-08741-9

Transmitting image data without losing significant information is challenging for any network application especially when large color images are transmitted through TCP communication protocol. This is due to network limitations such as buffer overflo... Read More about Saliency-based bit plane detection for network applications.

A Novel Character Segmentation-Reconstruction Approach for License Plate Recognition (2019)
Journal Article
Khare, V., Shivakumara, P., Seng Chan, C., Lu, T., Kim Meng, L., Hock Woon, H., & Blumenstein, M. (2019). A Novel Character Segmentation-Reconstruction Approach for License Plate Recognition. Expert systems with applications, 131, 219-239. https://doi.org/10.1016/j.eswa.2019.04.030

Developing an automatic license plate recognition system that can cope with multiple factors is challenging and interesting in the current scenario. In this paper, we introduce a new concept called partial character reconstruction to segment characte... Read More about A Novel Character Segmentation-Reconstruction Approach for License Plate Recognition.

Rough-fuzzy based scene categorization for text detection and recognition in video (2018)
Journal Article
Roy, S., Shivakumara, P., Jain, N., Khare, V., Dutta, A., Pal, U., & Lu, T. (2018). Rough-fuzzy based scene categorization for text detection and recognition in video. Pattern recognition, 80, 64-82. https://doi.org/10.1016/j.patcog.2018.02.014

Scene image or video understanding is a challenging task especially when number of video types increases drastically with high variations in background and foreground. This paper proposes a new method for categorizing scene videos into different clas... Read More about Rough-fuzzy based scene categorization for text detection and recognition in video.