INSTITUTIONAL DIGITAL REPOSITORY

Browsing by Author "Hambarde, P."

Browsing by Author "Hambarde, P."

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  • DarkGAN: Night image enhancement using generative adversarial networks 
    Alaspure, P.; Hambarde, P.; Dudhane, A.; Murala, S. (2022-12-20)
    Low light image enhancement is one of the challenging tasks in computer vision, and it becomes more difficult when images are very dark. Recently, most of low light image enhancement work is done either on synthetic data ...
  • Deep learning based approaches for single image depth estimation 
    Hambarde, P. (2022-10-26)
    Depth estimation is an important computer vision low-level information important for tasks such as 3D reconstruction, augmented reality, image de-hazing, semantic segmentation, object detection, human action recognition ...
  • Deep underwater image restoration and beyond 
    Dudhane, A.; Hambarde, P.; Patil, P.; Murala, S. (2021-07-01)
    Underwater image restoration is a challenging problem due to the multiple distortions. Degradation in the information is mainly due to the 1) light scattering effect 2) wavelength dependent color attenuation and 3) object ...
  • Eff-UNet++: A novel architecture for plant leaf segmentation and counting 
    Bhagat, S.; Kokare, M.; Haswani, V.; Hambarde, P.; Kamble, R. (2022-07-21)
    Leaf segmentation learns more about leaf-level traits such as leaf area, count, stress, and development phases. In plant phenotyping, segmentation and counting of plant organs like leaves are a major challenge due to ...
  • Robust unseen video understanding for various surveillance environments 
    Patil, P.; Singh, J.; Hambarde, P.; Kulkarni, A.; Chaudhary, S.; Murala, S. (2022-12-15)
    Automated video-based applications are a highly demanding technique from a security perspective, where detection of moving objects i.e., moving object segmentation (MOS) is performed. Therefore, we have proposed an effective ...
  • S2DNet: depth estimation from single image and sparse samples 
    Hambarde, P.; Murala, S. (2021-07-04)
    Depth prediction from single image is a challenging task due to the intra scale ambiguity and unavailability of prior information. The prediction of an unambiguous depth from single RGB image is very important aspect for ...
  • Single image depth estimation using deep adversarial training 
    Hambarde, P.; Dudhane, A.; Murala, S. (2021-08-20)
    Scene understanding is an active area of research in computer vision that encompasses several different problems. The LiDARs and stereo depth sensor have their own restrictions such as light sensitiveness, power ...
  • UW-GAN: single image depth estimation and image enhancement for underwater images 
    Hambarde, P.; Murala, S.; Dhall, A. (2021-12-06)
    Due to the unavailability of large-scale underwater depth image datasets and ill-posed problems, underwater single-image depth prediction is a challenging task. An unambiguous depth prediction for single underwater image is ...
  • Varicolored image De-hazing 
    Dudhane, A.; Biradar, K.; Patil, P.; Hambarde, P.; Murala, S. (2021-07-04)
    The quality of images captured in bad weather is often affected by chromatic casts and low visibility due to the presence of atmospheric particles. Restoration of the color balance is often ignored in most of the existing ...
  • WheatNet-lite: A novel light weight network for wheat head detection 
    Bhagat, S.; Kokare, M.; Haswani, V.; Hambarde, P.; Kamble, R. (2022-08-26)
    Recently, the potential for wheat head detection has been significantly enhanced using deep learning techniques. However, the significant challenges are variation in growth stages of wheat heads, canopy, genotype, and wheat ...