Majid Ali

University of Gujrat, Software Engineering, Graduate Student

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I am a dedicated Software Engineer with a BS degree in Software Engineering and over 3 years of professional experience. My expertise lies in Artificial Intelligence, Machine Learning, Natural Language Processing, Computer Vision, ChatBots, and Neural Networks. With a strong foundation in both front-end and back-end development, I have successfully developed and deployed complex applications using cutting-edge technologies. I am passionate about leveraging AI to solve real-world problems and continuously strive to enhance my skills and knowledge in this dynamic field.
Phone: +923029456798

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Kinetics of antibody response of calves immunized with Schistosoma mansoni glutathione-S-transferase

VETERINARSKI ARHIV, 2003

Six calves were immunized with Schistosoma mansoni glutathione-S-transferase (GST) antigen vaccin... more Six calves were immunized with Schistosoma mansoni glutathione-S-transferase (GST) antigen vaccine, expressed in E. coli (GST-coli) or yeast (GST-yeast). Six calves were injected with extracts of E. coli or yeast and kept as controls. Two experimentally infected calves were kept as source of infection and to provide positive antiserum to Schistosoma bovis. Kinetics of antibody response of the immunized calves was monitored by Western blots and enzyme-linked immunosorbent assay (ELISA). Using Western blots, the immunized calves produced specific IgG antibodies, which recognized S. mansoni GST (S.mGST) antigen, whereas the control calves did not. Using ELISA, antibodies to S.mGST antigen were detected in sera from S.mGSTcoli and GST-yeast vaccinated calves, but not in sera from control calves or S. bovis experimentally infected calves. In addition, the ELISA failed to detect S.mGST specific antibodies in sera from immunized calves or their controls when S. bovis adult worm extract was used as an antigen. The results of this study indicated that S.mGST antigen has no diagnostic potential for detection of bovine schistosomosis, caused by S. bovis infection, in susceptible ruminants.

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CNN Design for Traffic Signs Recognition and Translation

Majid Ali, 2022

Recognition of traffic signs is vary important in many applications such as in self-driving car/d... more Recognition of traffic signs is vary important in many applications such as in self-driving car/driverless car, traffic mapping and traffic surveillance. Recently, deep learning models demonstrated prominent representation capacity, and achieved outstanding performance in traffic sign recognition. In this paper, we propose a traffic sign recognition system by applying convolutional neural network (CNN)[15]. In comparison with previous methods which usually use CNN as feature extractor and multi-layer perception (MLP) as classifier, we proposed max pooling positions (MPPs) as an effective discriminative feature to predict category labels. Through extensive experiments, MPPs demonstrates the ideal characteristics of small inter-class variance and large intra-class variance. Moreover, with the German Traffic Sign Recognition Benchmark (GTSRB), outstanding performance has been achieved by using MPPs [1].

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Kinetics of antibody response of calves immunized with Schistosoma mansoni glutathione-S-transferase

VETERINARSKI ARHIV, 2003

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CNN Design for Traffic Signs Recognition and Translation

Majid Ali, 2022

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Majid Ali

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