In order to detect the object and inspect the road conditions in real-time, the 2-dimensional (2D) and 3dimensional (3D) data obtained from the onboard sensors, LiDAR and digital cameras are analyzed for object recognition to assist driving. Due to the uncertainties of the dynamic objects, such as pedestrians, animals or vibrated vehicles, extraction of complete and clear objects from LiDARs datasets requires complex post-processing since LiDAR data can be used for scanning at long distances, i.e., 300m, which can alarm the driver timely to take necessary actions. The dynamic and static objects from the LiDARs point clouds can be detected with the teacher-student framework algorithm along with the KITTI dataset. Furthermore, a semi-supervised theory is utilized to improve detection performance.
Colon also named large bowel and large intestine is the lowest part of human gastrointestinal tract. It is the third most common cancer in the world, and its rate of reported cases are continuously increasing. Colonoscopy is now the golden standard for detecting and removing the precancerous polyps. Manually endoscopy data analysis needs a lot of concentration and can be inaccurate at times. In this research work, an efficient Xception (E-Xception) model is trained for the detection of endoscopy absurdities in various areas of colon. We freeze the weights and biases of the model to use in our own model. In early detection of CRC, the fine-tune configuration has obtained 99.46% accuracy.
Cosmetic products are very important for women. Nowadays women are very conscious while purchasing their products. Women use a vast variety of cosmetic products, such as soap, shampoo, perfume, skincare or make-up. In Pakistan nowadays many cosmetic product companies advertise their products as a need which eventually appeals to a vast majority of women. Many companies use different social applications for advertisements. The Facebook application was selected as a medium for advertisement. This research study includes an analysis of the exposure to social media advertisements regarding cosmetics and purchasing behaviour of women. Specifically, this investigation is based on this specific objective. The research reveals that women are affected by social media advertisements. The study was anchored on the hierarchy of effect model. The target population comprised women. A simple random sampling technique was used. The survey method was used in the research study. Data were analyzed descriptively. The study revealed that social media advertisements affected the attitude and beliefs of women.
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