Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Nambiar, Athira"'
Sonar image synthesis is crucial for advancing applications in underwater exploration, marine biology, and defence. Traditional methods often rely on extensive and costly data collection using sonar sensors, jeopardizing data quality and diversity. T
Externí odkaz:
http://arxiv.org/abs/2410.08612
Deep learning techniques have revolutionized image classification by mimicking human cognition and automating complex decision-making processes. However, the deployment of AI systems in the wild, especially in high-security domains such as defence, i
Externí odkaz:
http://arxiv.org/abs/2408.12837
Autor:
S, Kamal Basha, Nambiar, Athira
Acoustic sonar imaging systems are widely used for underwater surveillance in both civilian and military sectors. However, acquiring high-quality sonar datasets for training Artificial Intelligence (AI) models confronts challenges such as limited dat
Externí odkaz:
http://arxiv.org/abs/2408.12833
Deep Neural Networks (DNNs) have revolutionized various fields by enabling task automation and reducing human error. However, their internal workings and decision-making processes remain obscure due to their black box nature. Consequently, the lack o
Externí odkaz:
http://arxiv.org/abs/2408.12808
Autor:
Mandalika, Sriram, Nambiar, Athira
Most of the sophisticated AI models utilize huge amounts of annotated data and heavy training to achieve high-end performance. However, there are certain challenges that hinder the deployment of AI models "in-the-wild" scenarios, i.e., inefficient us
Externí odkaz:
http://arxiv.org/abs/2408.04482
Biometrics plays a significant role in vision-based surveillance applications. Soft biometrics such as gait is widely used with face in surveillance tasks like person recognition and re-identification. Nevertheless, in practical scenarios, classical
Externí odkaz:
http://arxiv.org/abs/2303.13814
Autor:
Subramaniam, Arulkumar, Vaidya, Jayesh, Ameen, Muhammed Abdul Majeed, Nambiar, Athira, Mittal, Anurag
Video-based computer vision tasks can benefit from estimation of the salient regions and interactions between those regions. Traditionally, this has been done by identifying the object regions in the images by utilizing pre-trained models to perform
Externí odkaz:
http://arxiv.org/abs/2111.07370
Face is one of the predominant means of person recognition. In the process of ageing, human face is prone to many factors such as time, attributes, weather and other subject specific variations. The impact of these factors were not well studied in th
Externí odkaz:
http://arxiv.org/abs/2106.07696
Autor:
Dakshinamoorthy Putchen, Deepalakshmi, Nambiar, Athira, Ashok Menon, Aswathy, Jayaram, Ananthvikas, Ramaprasad, Sujay
Publikováno v:
In Journal of Mass Spectrometry and Advances in the Clinical Lab April 2024 32:18-23
Practical autonomous driving systems face two crucial challenges: memory constraints and domain gap issues. In this paper, we present a novel approach to learn domain adaptive knowledge in models with limited memory, thus bestowing the model with the
Externí odkaz:
http://arxiv.org/abs/2011.08007