Search Results - "Kamal, Suraj"

Passive sonar automated target classifier for shallow waters using end-to-end learnable deep convolutional LSTMs by Kamal, Suraj, Satheesh Chandran, C., Supriya, M.H.

“…Automated target recognition systems are increasingly employed in sonar systems to reduce manning and associated challenges. Although passive acoustic target…”
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Multiclass Image Segmentation using Deep Residual Encoder-Decoder Models in Highly Turbid Underwater Ambiances by Haridas, T. P. Mithun, Kamal, Suraj, Balakrishnan, Arun A., Thomas, Rosemol, Nezla, N. A., Balakrishnan, Kannan, Supriya, M. H.

“…Underwater environments, especially the coral reefs, are the habitat of many critically endangered species. Extensive monitoring of these aquatic ecosystems is…”
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Generative adversarial learning for improved data efficiency in underwater target classification by C., Satheesh Chandran, Kamal, Suraj, Mujeeb, A., M.H., Supriya

“…In the realms of the ocean, it becomes a formidable task to detect and classify the passive acoustic targets from the convoluted acoustic mixture confronted by…”
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Transformer-based temporal sequence learners for arrhythmia classification by Varghese, Ann, Kamal, Suraj, Kurian, James

“…An electrocardiogram (ECG) plays a crucial role in identifying and classifying cardiac arrhythmia. Traditional methods employ handcrafted features, and more…”
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Example-driven trajectory learner for robots under structured static environment by Sylaja, Midhun Muraleedharan, Kamal, Suraj, Kurian, James

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Passive Sonar Target Classification Using Deep Generative \beta -VAE by Satheesh, C., Kamal, Suraj, Mujeeb, A., Supriya, M. H.

“…The intrinsic complexity associated with passive sonar data makes the task of target recognition extremely challenging. The conventional classifier…”
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Passive Sonar Target Classification Using Deep Generative [Formula Omitted]-VAE by Satheesh, C, Kamal, Suraj, Mujeeb, A, Supriya, M H

“…The intrinsic complexity associated with passive sonar data makes the task of target recognition extremely challenging. The conventional classifier…”
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Facial Emotion Recognition Using Deep Convolutional Neural Network by Pranav, E., Kamal, Suraj, Satheesh Chandran, C., Supriya, M.H.

“…The rapid growth of artificial intelligence has contributed a lot to the technology world. As the traditional algorithms failed to meet the human needs in real…”
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Dehazing Underwater Images Using Encoder Decoder Based Generic Model-Agnostic Convolutional Neural Network by Thomas, Rosemol, Thampi, Lidiya, Kamal, Suraj, Balakrishnan, Arun A., Mithun Haridas, T. P., Supriya, M. H.

“…Enhancing degraded underwater images is a challenging problem for researchers. Deep learning approaches can significantly provide improvement in image…”
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Analysis of U-Net Based Image Segmentation Model on Underwater Images of Different Species of Fishes by Thampi, Lidiya, Thomas, Rosemol, Kamal, Suraj, Balakrishnan, Arun A., Mithun Haridas, T. P., Supriya, M. H.

“…Image segmentation is one of the key tasks for image processing in robotic vision, navigation, virtual reality, and augmented reality. Segmentation in…”
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Binaural Listening based DOA Estimation of Underwater Targets using Unsupervised GMM by Thomas, Linda, Simon, Blessy C, Satheesh Chandran, C., Kamal, Suraj, Supriya, M.H.

“…Highly accurate estimation of Direction of Arrival (DOA) of underwater targets with less number of hydrophones has always remained a challenging problem among…”
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Deep learning architectures for underwater target recognition by Kamal, Suraj, Mohammed, Shameer K., Pillai, P. R. Saseendran, Supriya, M. H.

“…Passive sonar target recognition is a challenging task due to the complex milieu of the ocean. Most of the state of the art target recognition systems depend…”
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Acoustic Source Localization using Random Forest Regressor by Pillai, Minu A., Ghosh, Alwyn, Joy, Jestin, Kamal, Suraj, Satheesh, Chandran C., Balakrishnan, Arun A., Supriya, M. H.

“…In this paper, a machine learning based acoustic source localization in an indoor environment is presented. Acoustic source localization is considered as a…”
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Prototype Implementation of Spatial Filtering using Sensor Array by Rashida, K., Kamal, Suraj, Satheesh Chandran, C., Balakrishnan, Arun A., Supriya, M. H.

“…A prototype implementation of spatial filtering based on a far-field plane wave incident on an equally spaced linear microphone array is described in this…”
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Spread spectrum based encrypted audio steganographic system with improved security by Krishnan, A. Anjana, Chandran, C. Satheesh, Kamal, Suraj, Supriya, M.H.

“…With rapid growth of the internet technology, steganography has gained increasing attention in the domain of information security. Audio steganography is a…”
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An l 2-norm regularized underwater target classifier with improved generalization capability by Chandran, C. Satheesh, Kamal, Suraj, Mujeeb, A., Supriya, M.H.

“…Improving the generalization capability of a target classifier has become one of the primary challenges in underwater target recognition systems. This paper…”
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Novel class detection of underwater targets using Self-Organizing neural networks by Chandran C, Satheesh, Kamal, Suraj, Mujeeb, A., Supriya, M. H.

“…An underwater target classifier can be trained only with the available limited instances of different ship and submarine emanations but in complex real world…”
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Implementation of an underwater image classifier using neural networks by Sabna, N., Kamal, S., Supriya, M. H., Pillai, P. R. S.

“…It is often very difficult to classify the obscured underwater images with robust success rates using classical statistical algorithmic approaches. For such…”
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Mitigating ambient noise in underwater acoustic receivers using independent component analysis by Kamal, S., Supriya, M. H., Pillai, P. R. S.

“…The acoustic ambience of the ocean is extremely turbid with a myriad of heterogeneous competing sources, of both manmade and natural origin. The cumulative…”
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Blind source separation of nonlinearly mixed ocean acoustic signals using Slow Feature Analysis by Kamal, S., Supriya, M. H., Pillai, P. R. S.

“…The ocean acoustic environment is astoundingly complex, consisting of numerous noise sources like ships, offshore oil rigs, marine life, shore waves and…”
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