Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Haloi, Mrinal"'
Recent deep learning approaches in table detection achieved outstanding performance and proved to be effective in identifying document layouts. Currently, available table detection benchmarks have many limitations, including the lack of samples diver
Externí odkaz:
http://arxiv.org/abs/2209.09207
In this paper, we present a passive method to detect face presentation attack a.k.a face liveness detection using an ensemble deep learning technique. Face liveness detection is one of the key steps involved in user identity verification of customers
Externí odkaz:
http://arxiv.org/abs/2201.08901
Autor:
Haloi, Mrinal
In this work, we propose an advanced AI based grading system for OCT images. The proposed system is a very deep fully convolutional attentive classification network trained with end to end advanced transfer learning with online random augmentation. I
Externí odkaz:
http://arxiv.org/abs/1812.07105
In this work, we propose advanced pneumonia and Tuberculosis grading system for X-ray images. The proposed system is a very deep fully convolutional classification network with online augmentation that outputs confidence values for diseases prevalenc
Externí odkaz:
http://arxiv.org/abs/1807.03120
Autor:
Haloi, Mrinal
Deep convolutional semantic segmentation (DCSS) learning doesn't converge to an optimal local minimum with random parameters initializations; a pre-trained model on the same domain becomes necessary to achieve convergence.In this work, we propose a j
Externí odkaz:
http://arxiv.org/abs/1710.07991
Autor:
Haloi, Mrinal
Generalization error defines the discriminability and the representation power of a deep model. In this work, we claim that feature space design using deep compositional function plays a significant role in generalization along with explicit and impl
Externí odkaz:
http://arxiv.org/abs/1706.01983
Matching pedestrians across multiple camera views, known as human re-identification, is a challenging research problem that has numerous applications in visual surveillance. With the resurgence of Convolutional Neural Networks (CNNs), several end-to-
Externí odkaz:
http://arxiv.org/abs/1607.08378
In this work, we have presented a novel method for detection of retinal image features, the optic disc and the fovea, from colour fundus photographs of dilated eyes for Computer-aided Diagnosis(CAD) system. A saliency map based method was used to det
Externí odkaz:
http://arxiv.org/abs/1601.06608
Autor:
Haloi, Mrinal
In this work, we propose a novel deep network for traffic sign classification that achieves outstanding performance on GTSRB surpassing all previous methods. Our deep network consists of spatial transformer layers and a modified version of inception
Externí odkaz:
http://arxiv.org/abs/1511.02992
Autor:
Haloi, Mrinal
In this work, we propose a novel microaneurysm (MA) detection for early diabetic retinopathy screening using color fundus images. Since MA usually the first lesions to appear as an indicator of diabetic retinopathy, accurate detection of MA is necess
Externí odkaz:
http://arxiv.org/abs/1505.04424