Kingshuk Chatterjee

Abstract: Bengali is the sixth most popular spoken language in the world. Computerized detection of handwritten Bengali (Bangla Lekha) character is very difficult due to the diversity and veracity of characters. In this paper, we have proposed a modified state-of-the-art deep learning to tackle the problem of Bengali handwritten character recognition. This method used the lesser number of iterations to train than other comparable methods. The transfer learning on Resnet-50 deep convolutional neural network model is used on pretrained ImageNet dataset. One cycle policy is modified with varying the input image sizes to ensure faster training. Proposed method executed on BanglaLekha-Isolated dataset for evaluation that consists of 84 classes (50 Basic, 10 Numerals and 24 Compound Characters). We have achieved 97.12% accuracy in just 47 epochs. Proposed method gives very good results in terms of epoch and accuracy compare to other recent methods by considering number of classes. Without ensembling, proposed solution achieves state-of-the-art result and shows the effectiveness of ResNet-50 for classification of Bangla HCR.

Abstract: Watson---Crick automata are finite automata working on double strands. Extensive research work has already been done on non-deterministic Watson---Crick automata and on deterministic Watson---Crick automata. State complexity of Watson---Crick automata has also been discussed. In this paper we analyze the state complexity of deterministic Watson---Crick automata with respect to non-deterministic block automata and non-deterministic finite automata. We also introduce new finite automata combining the properties of Watson---Crick automata and time varying automata. These automata have the unique property that the 1-limited stateless variant of these automata have the power to count. We further discuss the state complexity of time varying automata and time varying Watson---Crick automata.

Abstract: For any observer of sports in South Asia, Cricket seems to take the pride of place because it is the game in which sportspersons from this part of the world have given innumerable impressive performances at the international level with some degree of consistency. And, of all the jousts on the pitches of South Asia, any contest between the teams of India and Pakistan seems to enjoy a degree of public interest that no other match can ever hope to equal. Having a match between India and Pakistan guarantees packed stadiums and empty streets. Cricket series between India and Pakistan have frequently caused major issues of public debate over the past decade. Beginning with escalation of militancy in Kashmir in the mid-1990s, and culminating during the Kargil war (1999), a semi-consensus emerged that India should not play with Pakistan on either Indian and Pakistani soil while people are dying due to Pakistan's subversive activities. Even though an overwhelming majority of India's cricketing enthusiasts show more interest on any match with Pakistan, the government's reluctance to let normal sporting relations continue has evoked little or no debate, let alone protest. This could be taken as an indication that there is really no intrinsic interest in Indo-Pak matches, that the media create the hype for their own interest in creating news; but that would fail to account for the absence of debate on this issue even in forums outside media circles. Still more interesting is the fact that once the government began to endorse the idea of resumption of Indo-Pak cricket, there were gestures of approval from across the country for the government's stand. In a democracy as fractious as that of India, such a level of agreement with the government's stand on any issue is unique more so because of the willing participation of the media. This might be a testimony to the present government's successful manufacture of consent over the issue

Abstract: Recently, a few works on recognition of handwritten Bangla characters have been reported in the literature. However, there is scope for further research in this area. In the present article, results of our recent study on recognition of handwritten Bangla basic characters will be reported. This is a 50 class problem since the alphabet of Bangla has 50 basic characters. In this study, features are obtained by computing local chain code histograms of input character shape. Comparative recognition results are obtained between computation of the above feature based on the contour and one-pixel skeletal representations of the input character image. Also, the classification results are obtained after down sampling the histogram feature by applying Gaussian filter in both these cases. Multilayer perceptrons (MLP) trained by back propagation (BP) algorithm are used as classifiers in the present study. Near exhaustive studies are done for selection of its hidden layer size. An analysis of the misclassified samples shows an interesting error pattern and this has been used for further improvement in the recognition results. Final recognition accuracies on the training and the test sets are respectively 94.65% and 92.14%.

Abstract: Tumor segmentation from magnetic resonance imaging (MRI) data is an important but time consuming manual task performed by medical experts. Automating this process is a challenging task because of the high diversity in the appearance of tumor tissues among different patients and in many cases similarity with the normal tissues. MRI is an advanced medical imaging technique providing rich information about the human soft-tissue anatomy. There are different brain tumor detection and segmentation methods to detect and segment a brain tumor from MRI images. These detection and segmentation approaches are reviewed with an importance placed on enlightening the advantages and drawbacks of these methods for brain tumor detection and segmentation. The use of MRI image detection and segmentation in different procedures are also described. Here a brief review of different segmentation for detection of brain tumor from MRI of brain has been discussed.

Abstract: This book attempts to bridge the gap between aphasia research and the rehabilitation of patients with this language disorder, making explicit the relationship between what is being rehabilitated and how to rehabilitate it. The author has run an aphasia rehabilitation unit for more than thirty years and draws on her considerable experience to provide researchers, clinicians, and their students and trainees in speech-language pathology and therapy, aphasiology, and neuropsychology with comprehensive coverage of the evolution and state of the art aphasia research and therapy.